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ORIGINAL ARTICLE

Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases

Janowczyk Andrew, Madabhushi Anant

Year : 2016| Volume: 7| Issue : 1 | Page no: 29-29

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International Journal of Imaging Systems and Technology. 2022;
[Pubmed]  [Google Scholar] [DOI]
2 Breast histopathological image analysis using image processing techniques for diagnostic puposes: A methodological review
R Rashmi, Keerthana Prasad, Chethana Babu K Udupa
Journal of Medical Systems. 2022; 46(1)
[Pubmed]  [Google Scholar] [DOI]
3 A new lightweight convolutional neural network for radiation-induced liver disease classification
Demet Alici-Karaca, Bahriye Akay, Arzu Yay, Pinar Suna, O. Ufuk Nalbantoglu, Dervis Karaboga, Alper Basturk, Esra Balcioglu, Munevver Baran
Biomedical Signal Processing and Control. 2022; 73: 103463
[Pubmed]  [Google Scholar] [DOI]
4 Self supervised contrastive learning for digital histopathology
Ozan Ciga, Tony Xu, Anne Louise Martel
Machine Learning with Applications. 2022; 7: 100198
[Pubmed]  [Google Scholar] [DOI]
5 Mini-batch optimization enables training of ODE models on large-scale datasets
Paul Stapor, Leonard Schmiester, Christoph Wierling, Simon Merkt, Dilan Pathirana, Bodo M. H. Lange, Daniel Weindl, Jan Hasenauer
Nature Communications. 2022; 13(1)
[Pubmed]  [Google Scholar] [DOI]
6 StackBC: Deep learning and transfer learning techniques based stacking approach for accurate Invasive Ductal Carcinoma classification using histology images
Amin Ul Haq, Jian Ping Li, Samad Wali, Sultan Ahmad, Zafar Ali, Jalaluddin Khan, Ajab Khan, Amjad Ali
Journal of Intelligent & Fuzzy Systems. 2022; : 1
[Pubmed]  [Google Scholar] [DOI]
7 An Efficient Multi-Level Convolutional Neural Network Approach for White Blood Cells Classification
César Cheuque, Marvin Querales, Roberto León, Rodrigo Salas, Romina Torres
Diagnostics. 2022; 12(2): 248
[Pubmed]  [Google Scholar] [DOI]
8 A Deep Learning Convolutional Neural Network Can Differentiate Between Helicobacter Pylori Gastritis and Autoimmune Gastritis With Results Comparable to Gastrointestinal Pathologists
Michael M. Franklin, Fred A. Schultz, Marissa A. Tafoya, Audra A. Kerwin, Cory J. Broehm, Edgar G. Fischer, Rama R. Gullapalli, Douglas P. Clark, Joshua A. Hanson, David R. Martin
Archives of Pathology & Laboratory Medicine. 2022; 146(1): 117
[Pubmed]  [Google Scholar] [DOI]
9 Pathologist Concordance for Ovarian Carcinoma Subtype Classification and Identification of Relevant Histologic Features Using Microscope and Whole Slide Imaging
Marios A. Gavrielides, Brigitte M. Ronnett, Russell Vang, Stephanie Barak, Elsie Lee, Paul N. Staats, Erik Jenson, Priya Skaria, Fahime Sheikhzadeh, Meghan Miller, Ian S. Hagemann, Nicholas Petrick, Jeffrey D. Seidman
Archives of Pathology & Laboratory Medicine. 2021; 145(12): 1516
[Pubmed]  [Google Scholar] [DOI]
10 Liver Pathologic Changes After Direct-Acting Antiviral Agent Therapy and Sustained Virologic Response in the Setting of Chronic Hepatitis C Virus Infection
Romulo Celli, Saad Saffo, Saleem Kamili, Nicholas Wiese, Tonya Hayden, Tamar Taddei, Dhanpat Jain
Archives of Pathology & Laboratory Medicine. 2021; 145(4): 419
[Pubmed]  [Google Scholar] [DOI]
11 Enjeux expérimentiels de l'utilistion de l'IA en anatomopathologie
Laurent Collet, Michel Durampart, Laurent Heiser, Ludovic Picard
Communiquer. Revue de communication sociale et publique. 2021; (33): 26
[Pubmed]  [Google Scholar] [DOI]
12 TISSUE CLASSIFICATION FOR COLORECTAL CANCER UTILIZING TECHNIQUES OF DEEP LEARNING AND MACHINE LEARNING
Kasikrit Damkliang, Thakerng Wongsirichot, Paramee Thongsuksai
Biomedical Engineering: Applications, Basis and Communications. 2021; 33(03): 2150022
[Pubmed]  [Google Scholar] [DOI]
13 Automated cervical digitized histology whole-slide image analysis toolbox
Sudhir Sornapudi, Ravitej Addanki, RJoe Stanley, WilliamV Stoecker, Rodney Long, Rosemary Zuna, ShellaineR Frazier, Sameer Antani
Journal of Pathology Informatics. 2021; 12(1): 26
[Pubmed]  [Google Scholar] [DOI]
14 A Bidirectional Long Short-Term Memory Model Algorithm for Predicting COVID-19 in Gulf Countries
Theyazn H. H. Aldhyani, Hasan Alkahtani
Life. 2021; 11(11): 1118
[Pubmed]  [Google Scholar] [DOI]
15 On the Scale Invariance in State of the Art CNNs Trained on ImageNet
Mara Graziani, Thomas Lompech, Henning Müller, Adrien Depeursinge, Vincent Andrearczyk
Machine Learning and Knowledge Extraction. 2021; 3(2): 374
[Pubmed]  [Google Scholar] [DOI]
16 Deeply Supervised UNet for Semantic Segmentation to Assist Dermatopathological Assessment of Basal Cell Carcinoma
Jean Le’Clerc Arrastia, Nick Heilenkötter, Daniel Otero Baguer, Lena Hauberg-Lotte, Tobias Boskamp, Sonja Hetzer, Nicole Duschner, Jörg Schaller, Peter Maass
Journal of Imaging. 2021; 7(4): 71
[Pubmed]  [Google Scholar] [DOI]
17 Classification of Diffuse Glioma Subtype from Clinical-Grade Pathological Images Using Deep Transfer Learning
Sanghyuk Im, Jonghwan Hyeon, Eunyoung Rha, Janghyeon Lee, Ho-Jin Choi, Yuchae Jung, Tae-Jung Kim
Sensors. 2021; 21(10): 3500
[Pubmed]  [Google Scholar] [DOI]
18 Biomedical Image Processing and Classification
Luca Mesin
Electronics. 2021; 10(1): 66
[Pubmed]  [Google Scholar] [DOI]
19 Deep Learning Techniques for the Classification of Colorectal Cancer Tissue
Min-Jen Tsai, Yu-Han Tao
Electronics. 2021; 10(14): 1662
[Pubmed]  [Google Scholar] [DOI]
20 Deep Learning on Histopathology Images for Breast Cancer Classification: A Bibliometric Analysis
Siti Khairi, Mohd Bakar, Sakhinah Bakar, Nurwahyuna Rosli
Healthcare. 2021; 10(1): 10
[Pubmed]  [Google Scholar] [DOI]
21 A Deep Neural Network-Based Method for Prediction of Dementia Using Big Data
Jungyoon Kim, Jihye Lim
International Journal of Environmental Research and Public Health. 2021; 18(10): 5386
[Pubmed]  [Google Scholar] [DOI]
22 Deep Learning in Pancreatic Tissue: Identification of Anatomical Structures, Pancreatic Intraepithelial Neoplasia, and Ductal Adenocarcinoma
Mark Kriegsmann, Katharina Kriegsmann, Georg Steinbuss, Christiane Zgorzelski, Anne Kraft, Matthias M. Gaida
International Journal of Molecular Sciences. 2021; 22(10): 5385
[Pubmed]  [Google Scholar] [DOI]
23 Quantification of the Immune Content in Neuroblastoma: Deep Learning and Topological Data Analysis in Digital Pathology
Nicole Bussola, Bruno Papa, Ombretta Melaiu, Aurora Castellano, Doriana Fruci, Giuseppe Jurman
International Journal of Molecular Sciences. 2021; 22(16): 8804
[Pubmed]  [Google Scholar] [DOI]
24 Deep Learning for the Classification of Non-Hodgkin Lymphoma on Histopathological Images
Georg Steinbuss, Mark Kriegsmann, Christiane Zgorzelski, Alexander Brobeil, Benjamin Goeppert, Sascha Dietrich, Gunhild Mechtersheimer, Katharina Kriegsmann
Cancers. 2021; 13(10): 2419
[Pubmed]  [Google Scholar] [DOI]
25 A Review of Computer-Aided Expert Systems for Breast Cancer Diagnosis
Xin Yu Liew, Nazia Hameed, Jeremie Clos
Cancers. 2021; 13(11): 2764
[Pubmed]  [Google Scholar] [DOI]
26 A Comprehensive Survey on Deep-Learning-Based Breast Cancer Diagnosis
Muhammad Firoz Mridha, Md. Abdul Hamid, Muhammad Mostafa Monowar, Ashfia Jannat Keya, Abu Quwsar Ohi, Md. Rashedul Islam, Jong-Myon Kim
Cancers. 2021; 13(23): 6116
[Pubmed]  [Google Scholar] [DOI]
27 Klasifikasi Citra Histopatologi Kanker Payudara menggunakan Data Resampling Random dan Residual Network
Wahyudi Setiawan
JURNAL SISTEM INFORMASI BISNIS. 2021; 11(1): 70
[Pubmed]  [Google Scholar] [DOI]
28 Best Practice Recommendations for the Implementation of a Digital Pathology Workflow in the Anatomic Pathology Laboratory by the European Society of Digital and Integrative Pathology (ESDIP)
Filippo Fraggetta, Vincenzo L’Imperio, David Ameisen, Rita Carvalho, Sabine Leh, Tim-Rasmus Kiehl, Mircea Serbanescu, Daniel Racoceanu, Vincenzo Della Mea, Antonio Polonia, Norman Zerbe, Catarina Eloy
Diagnostics. 2021; 11(11): 2167
[Pubmed]  [Google Scholar] [DOI]
29 Detecting breast cancer using artificial intelligence: Convolutional neural network
Avishek Choudhury, Sunanda Perumalla
Technology and Health Care. 2021; 29(1): 33
[Pubmed]  [Google Scholar] [DOI]
30 Improved Classification of Cancerous Histopathology Images using Color Channel Separation and Deep Learning
Rachit Kumar Gupta, Jatinder Manhas
Journal of Multimedia Information System. 2021; 8(3): 175
[Pubmed]  [Google Scholar] [DOI]
31 Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images
Niccolň Marini, Sebastian Otálora, Damian Podareanu, Mart van Rijthoven, Jeroen van der Laak, Francesco Ciompi, Henning Müller, Manfredo Atzori
Frontiers in Computer Science. 2021; 3
[Pubmed]  [Google Scholar] [DOI]
32 Deep Learning in Head and Neck Tumor Multiomics Diagnosis and Analysis: Review of the Literature
Xi Wang, Bin-bin Li
Frontiers in Genetics. 2021; 12
[Pubmed]  [Google Scholar] [DOI]
33 Prediction of Breast Cancer Recurrence Using a Deep Convolutional Neural Network Without Region-of-Interest Labeling
Nam Nhut Phan, Chih-Yi Hsu, Chi-Cheng Huang, Ling-Ming Tseng, Eric Y. Chuang
Frontiers in Oncology. 2021; 11
[Pubmed]  [Google Scholar] [DOI]
34 Detection of Metastatic Tumor Cells in the Bone Marrow Aspirate Smears by Artificial Intelligence (AI)-Based Morphogo System
Pu Chen, Run Chen Xu, Nan Chen, Lan Zhang, Li Zhang, Jianfeng Zhu, Baishen Pan, Beili Wang, Wei Guo
Frontiers in Oncology. 2021; 11
[Pubmed]  [Google Scholar] [DOI]
35 Deep Learning of Histopathology Images at the Single Cell Level
Kyubum Lee, John H. Lockhart, Mengyu Xie, Ritu Chaudhary, Robbert J. C. Slebos, Elsa R. Flores, Christine H. Chung, Aik Choon Tan
Frontiers in Artificial Intelligence. 2021; 4
[Pubmed]  [Google Scholar] [DOI]
36 Histopathological Classification of Canine Cutaneous Round Cell Tumors Using Deep Learning: A Multi-Center Study
Massimo Salvi, Filippo Molinari, Selina Iussich, Luisa Vera Muscatello, Luca Pazzini, Silvia Benali, Barbara Banco, Francesca Abramo, Raffaella De Maria, Luca Aresu
Frontiers in Veterinary Science. 2021; 8
[Pubmed]  [Google Scholar] [DOI]
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Philipp TSCHANDL
Italian Journal of Dermatology and Venereology. 2021; 156(3)
[Pubmed]  [Google Scholar] [DOI]
38 A Hybrid Method Based on Feature Fusion for Breast Cancer Classification using Histopathological Images
Emre DANDIL, Ali Osman SELVI, Kerim Kürsat ÇEVIK, Mehmet Süleyman YILDIRIM, Süleyman UZUN
European Journal of Science and Technology. 2021;
[Pubmed]  [Google Scholar] [DOI]
39 An efficient glomerular object locator for renal whole slide images using proposal-free network and dynamic scale evaluation method
Xueyu Liu, Ming Li, Yongfei Wu, Yilin Chen, Fang Hao, Daoxiang Zhou, Chen Wang, Chuanfeng Ma, Guangze Shi, Xiaoshuang Zhou
AI Communications. 2021; : 1
[Pubmed]  [Google Scholar] [DOI]
40 Classification of Invasive Ductal Carcinoma from histopathology breast cancer images using Stacked Generalized Ensemble
Deepika Kumar, Usha Batra
Journal of Intelligent & Fuzzy Systems. 2021; 40(3): 4919
[Pubmed]  [Google Scholar] [DOI]
41 A Transfer Learning Architecture Based on a Support Vector Machine for Histopathology Image Classification
Jiayi Fan, JangHyeon Lee, YongKeun Lee
Applied Sciences. 2021; 11(14): 6380
[Pubmed]  [Google Scholar] [DOI]
42 A Whole-Slide Image Managing Library Based on Fastai for Deep Learning in the Context of Histopathology: Two Use-Cases Explained
Christoph Neuner, Roland Coras, Ingmar Blümcke, Alexander Popp, Sven M. Schlaffer, Andre Wirries, Michael Buchfelder, Samir Jabari
Applied Sciences. 2021; 12(1): 13
[Pubmed]  [Google Scholar] [DOI]
43 Shifting Gears in Precision Oncology—Challenges and Opportunities of Integrative Data Analysis
Ka-Won Noh, Reinhard Buettner, Sebastian Klein
Biomolecules. 2021; 11(9): 1310
[Pubmed]  [Google Scholar] [DOI]
44 DICOM Format and Protocol Standardization—A Core Requirement for Digital Pathology Success
David A. Clunie
Toxicologic Pathology. 2021; 49(4): 738
[Pubmed]  [Google Scholar] [DOI]
45 Using Deep Learning Artificial Intelligence Algorithms to Verify N-Nitroso-N-Methylurea and Urethane Positive Control Proliferative Changes in Tg-RasH2 Mouse Carcinogenicity Studies
Daniel Rudmann, Jay Albretsen, Colin Doolan, Mark Gregson, Beth Dray, Aaron Sargeant, Donal O’Shea D, Jogile Kuklyte, Adam Power, Jenny Fitzgerald
Toxicologic Pathology. 2021; 49(4): 938
[Pubmed]  [Google Scholar] [DOI]
46 Deep Learning in Toxicologic Pathology: A New Approach to Evaluate Rodent Retinal Atrophy
Maria Cristina De Vera Mudry, Jim Martin, Vanessa Schumacher, Raghavan Venugopal
Toxicologic Pathology. 2021; 49(4): 851
[Pubmed]  [Google Scholar] [DOI]
47 HistoNet: A Deep Learning-Based Model of Normal Histology
Holger Hoefling, Tobias Sing, Imtiaz Hossain, Julie Boisclair, Arno Doelemeyer, Thierry Flandre, Alessandro Piaia, Vincent Romanet, Gianluca Santarossa, Chandrassegar Saravanan, Esther Sutter, Oliver Turner, Kuno Wuersch, Pierre Moulin
Toxicologic Pathology. 2021; 49(4): 784
[Pubmed]  [Google Scholar] [DOI]
48 Retrospective analysis and time series forecasting with automated machine learning of ascariasis, enterobiasis and cystic echinococcosis in Romania
Johannes Benecke, Cornelius Benecke, Marius Ciutan, Mihnea Dosius, Cristian Vladescu, Victor Olsavszky, Kate Zinszer
PLOS Neglected Tropical Diseases. 2021; 15(11): e0009831
[Pubmed]  [Google Scholar] [DOI]
49 Deep Learning Model for Cell Nuclei Segmentation and Lymphocyte Identification in Whole Slide Histology Images
Elzbieta Budginaite, Mindaugas Morkunas, Arvydas Laurinavicius, Povilas Treigys
Informatica. 2021; : 23
[Pubmed]  [Google Scholar] [DOI]
50 Akciger Histopatoloji Görüntülerinden Çikarilan Derin Özellikleri Kullanan Makine Ögrenmesi Siniflandiricilari ile Akciger Kanseri Tespiti
Emine UÇAR
Bitlis Eren Üniversitesi Fen Bilimleri Dergisi. 2021;
[Pubmed]  [Google Scholar] [DOI]
51 Integrative multiomics-histopathology analysis for breast cancer classification
Yasha Ektefaie, William Yuan, Deborah A. Dillon, Nancy U. Lin, Jeffrey A. Golden, Isaac S. Kohane, Kun-Hsing Yu
npj Breast Cancer. 2021; 7(1)
[Pubmed]  [Google Scholar] [DOI]
52 Deep computational pathology in breast cancer
Andrea Duggento, Allegra Conti, Alessandro Mauriello, Maria Guerrisi, Nicola Toschi
Seminars in Cancer Biology. 2021; 72: 226
[Pubmed]  [Google Scholar] [DOI]
53 Digital pathology and artificial intelligence in translational medicine and clinical practice
Vipul Baxi, Robin Edwards, Michael Montalto, Saurabh Saha
Modern Pathology. 2021;
[Pubmed]  [Google Scholar] [DOI]
54 Deep learning in cancer pathology: a new generation of clinical biomarkers
Amelie Echle, Niklas Timon Rindtorff, Titus Josef Brinker, Tom Luedde, Alexander Thomas Pearson, Jakob Nikolas Kather
British Journal of Cancer. 2021; 124(4): 686
[Pubmed]  [Google Scholar] [DOI]
55 Morphological features of single cells enable accurate automated classification of cancer from non-cancer cell lines
Zeynab Mousavikhamene, Daniel J. Sykora, Milan Mrksich, Neda Bagheri
Scientific Reports. 2021; 11(1)
[Pubmed]  [Google Scholar] [DOI]
56 A multi-phase deep CNN based mitosis detection framework for breast cancer histopathological images
Anabia Sohail, Asifullah Khan, Noorul Wahab, Aneela Zameer, Saranjam Khan
Scientific Reports. 2021; 11(1)
[Pubmed]  [Google Scholar] [DOI]
57 A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks
Andrew Lagree, Majidreza Mohebpour, Nicholas Meti, Khadijeh Saednia, Fang-I. Lu, Elzbieta Slodkowska, Sonal Gandhi, Eileen Rakovitch, Alex Shenfield, Ali Sadeghi-Naini, William T. Tran
Scientific Reports. 2021; 11(1)
[Pubmed]  [Google Scholar] [DOI]
58 A generalized deep learning framework for whole-slide image segmentation and analysis
Mahendra Khened, Avinash Kori, Haran Rajkumar, Ganapathy Krishnamurthi, Balaji Srinivasan
Scientific Reports. 2021; 11(1)
[Pubmed]  [Google Scholar] [DOI]
59 CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance
Sara P. Oliveira, Pedro C. Neto, Joăo Fraga, Diana Montezuma, Ana Monteiro, Joăo Monteiro, Liliana Ribeiro, Sofia Gonçalves, Isabel M. Pinto, Jaime S. Cardoso
Scientific Reports. 2021; 11(1)
[Pubmed]  [Google Scholar] [DOI]
60 An empirical analysis of machine learning frameworks for digital pathology in medical science
S.K.B. Sangeetha, R Dhaya, Dhruv T Shah, R Dharanidharan, K. Praneeth Sai Reddy
Journal of Physics: Conference Series. 2021; 1767(1): 012031
[Pubmed]  [Google Scholar] [DOI]
61 High-performance deep learning pipeline predicts individuals in mixtures of DNA using sequencing data
Nam Nhut Phan, Amrita Chattopadhyay, Tsui-Ting Lee, Hsiang-I Yin, Tzu-Pin Lu, Liang-Chuan Lai, Hsiao-Lin Hwa, Mong-Hsun Tsai, Eric Y Chuang
Briefings in Bioinformatics. 2021; 22(6)
[Pubmed]  [Google Scholar] [DOI]
62 Artificial Intelligence and Mapping a New Direction in Laboratory Medicine: A Review
Daniel S Herman, Daniel D Rhoads, Wade L Schulz, Thomas J S Durant
Clinical Chemistry. 2021; 67(11): 1466
[Pubmed]  [Google Scholar] [DOI]
63 An automated computational image analysis pipeline for histological grading of cardiac allograft rejection
Eliot G Peyster, Sara Arabyarmohammadi, Andrew Janowczyk, Sepideh Azarianpour-Esfahani, Miroslav Sekulic, Clarissa Cassol, Luke Blower, Anil Parwani, Priti Lal, Michael D Feldman, Kenneth B Margulies, Anant Madabhushi
European Heart Journal. 2021; 42(24): 2356
[Pubmed]  [Google Scholar] [DOI]
64 An Imaging Biomarker of Tumor-Infiltrating Lymphocytes to Risk-Stratify Patients With HPV-Associated Oropharyngeal Cancer
Germán Corredor, Paula Toro, Can Koyuncu, Cheng Lu, Christina Buzzy, Kaustav Bera, Pingfu Fu, Mitra Mehrad, Kim A Ely, Mojgan Mokhtari, Kailin Yang, Deborah Chute, David J Adelstein, Lester D R Thompson, Justin A Bishop, Farhoud Faraji, Wade Thorstad, Patricia Castro, Vlad Sandulache, Shlomo A Koyfman, James S Lewis, Anant Madabhushi
JNCI: Journal of the National Cancer Institute. 2021;
[Pubmed]  [Google Scholar] [DOI]
65 Deep Learning-Based Image Classification in Differentiating Tufted Astrocytes, Astrocytic Plaques, and Neuritic Plaques
Shunsuke Koga, Nikhil B Ghayal, Dennis W Dickson
Journal of Neuropathology & Experimental Neurology. 2021; 80(4): 306
[Pubmed]  [Google Scholar] [DOI]
66 Artificial intelligence neuropathologist for glioma classification using deep learning on hematoxylin and eosin stained slide images and molecular markers
Lei Jin, Feng Shi, Qiuping Chun, Hong Chen, Yixin Ma, Shuai Wu, N U Farrukh Hameed, Chunming Mei, Junfeng Lu, Jun Zhang, Abudumijiti Aibaidula, Dinggang Shen, Jinsong Wu
Neuro-Oncology. 2021; 23(1): 44
[Pubmed]  [Google Scholar] [DOI]
67 Histopathology-led quality evaluation of endoluminal excision specimens – not a bad idea!
Marnix Jansen
Endoscopy. 2021;
[Pubmed]  [Google Scholar] [DOI]
68 Sliding window based deep ensemble system for breast cancer classification
Amin Alqudah, Ali Mohammad Alqudah
Journal of Medical Engineering & Technology. 2021; 45(4): 313
[Pubmed]  [Google Scholar] [DOI]
69 An Advanced Automated Image Analysis Model for Scoring of ER, PR, HER-2 and Ki-67 in Breast Carcinoma
Min Feng, Jie Chen, Xuhui Xiang, Yang Deng, Yanyan Zhou, Zhang Zhang, Zhongxi Zheng, Ji Bao, Hong Bu
IEEE Access. 2021; 9: 108441
[Pubmed]  [Google Scholar] [DOI]
70 Automatic Detection of Invasive Ductal Carcinoma Based on the Fusion of Multi-Scale Residual Convolutional Neural Network and SVM
Jianfei Zhang, Xiaoyan Guo, Bo Wang, Wensheng Cui
IEEE Access. 2021; 9: 40308
[Pubmed]  [Google Scholar] [DOI]
71 A Deep Learning Framework Integrating the Spectral and Spatial Features for Image-Assisted Medical Diagnostics
Susmita Ghosh, Swagatam Das, Rammohan Mallipeddi
IEEE Access. 2021; 9: 163686
[Pubmed]  [Google Scholar] [DOI]
72 Multi-Task Pre-Training of Deep Neural Networks for Digital Pathology
Romain Mormont, Pierre Geurts, Raphael Maree
IEEE Journal of Biomedical and Health Informatics. 2021; 25(2): 412
[Pubmed]  [Google Scholar] [DOI]
73 A Visually Interpretable Deep Learning Framework for Histopathological Image-Based Skin Cancer Diagnosis
Shancheng Jiang, Huichuan Li, Zhi Jin
IEEE Journal of Biomedical and Health Informatics. 2021; 25(5): 1483
[Pubmed]  [Google Scholar] [DOI]
74 A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises
S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos, James S. Duncan, Bram Van Ginneken, Anant Madabhushi, Jerry L. Prince, Daniel Rueckert, Ronald M. Summers
Proceedings of the IEEE. 2021; 109(5): 820
[Pubmed]  [Google Scholar] [DOI]
75 Small Blob Detector Using Bi-Threshold Constrained Adaptive Scales
Yanzhe Xu, Teresa Wu, Jennifer R. Charlton, Fei Gao, Kevin M. Bennett
IEEE Transactions on Biomedical Engineering. 2021; 68(9): 2654
[Pubmed]  [Google Scholar] [DOI]
76 MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge
Ruchika Verma, Neeraj Kumar, Abhijeet Patil, Nikhil Cherian Kurian, Swapnil Rane, Simon Graham, Quoc Dang Vu, Mieke Zwager, Shan E. Ahmed Raza, Nasir Rajpoot, Xiyi Wu, Huai Chen, Yijie Huang, Lisheng Wang, Hyun Jung, G. Thomas Brown, Yanling Liu, Shuolin Liu, Seyed Alireza Fatemi Jahromi, Ali Asghar Khani, Ehsan Montahaei, Mahdieh Soleymani Baghshah, Hamid Behroozi, Pavel Semkin, Alexandr Rassadin, Prasad Dutande, Romil Lodaya, Ujjwal Baid, Bhakti Baheti, Sanjay Talbar, Amirreza Mahbod, Rupert Ecker, Isabella Ellinger, Zhipeng Luo, Bin Dong, Zhengyu Xu, Yuehan Yao, Shuai Lv, Ming Feng, Kele Xu, Hasib Zunair, Abdessamad Ben Hamza, Steven Smiley, Tang-Kai Yin, Qi-Rui Fang, Shikhar Srivastava, Dwarikanath Mahapatra, Lubomira Trnavska, Hanyun Zhang, Priya Lakshmi Narayanan, Justin Law, Yinyin Yuan, Abhiroop Tejomay, Aditya Mitkari, Dinesh Koka, Vikas Ramachandra, Lata Kini, Amit Sethi
IEEE Transactions on Medical Imaging. 2021; 40(12): 3413
[Pubmed]  [Google Scholar] [DOI]
77 Visual Analytics for Hypothesis-Driven Exploration in Computational Pathology
A. Corvo, H. S. Garcia Caballero, M. A. Westenberg, M. A. van Driel, J. J. van Wijk
IEEE Transactions on Visualization and Computer Graphics. 2021; 27(10): 3851
[Pubmed]  [Google Scholar] [DOI]
78 Recent technical advances in whole slide imaging instrumentation
Prateek Katare, Sai Siva Gorthi
Journal of Microscopy. 2021; 284(2): 103
[Pubmed]  [Google Scholar] [DOI]
79 Current and future applications of artificial intelligence in pathology: a clinical perspective
Emad A Rakha, Michael Toss, Sho Shiino, Paul Gamble, Ronnachai Jaroensri, Craig H Mermel, Po-Hsuan Cameron Chen
Journal of Clinical Pathology. 2021; 74(7): 409
[Pubmed]  [Google Scholar] [DOI]
80 A comparative study on machine learning-based classification to find photothrombotic lesion in histological rabbit brain images
Sang Hee Jo, Yoonhee Kim, Yoon Bum Lee, Sung Suk Oh, Jong-ryul Choi
Journal of Innovative Optical Health Sciences. 2021; 14(06)
[Pubmed]  [Google Scholar] [DOI]
81 A Calibrated Multiexit Neural Network for Detecting Urothelial Cancer Cells
L. Lilli, E. Giarnieri, S. Scardapane, Nadia A. Chuzhanova
Computational and Mathematical Methods in Medicine. 2021; 2021: 1
[Pubmed]  [Google Scholar] [DOI]
82 Deep learning-based model for diagnosing Alzheimer's disease and tauopathies
Shunsuke Koga, Akihiro Ikeda, Dennis W. Dickson
Neuropathology and Applied Neurobiology. 2021;
[Pubmed]  [Google Scholar] [DOI]
83 Memory augmented convolutional neural network and its application in bioimages
Weiping Ding, Yurui Ming, Yu-Kai Wang, Chin-Teng Lin
Neurocomputing. 2021; 466: 128
[Pubmed]  [Google Scholar] [DOI]
84 Development and evaluation of deep learning–based segmentation of histologic structures in the kidney cortex with multiple histologic stains
Catherine P. Jayapandian, Yijiang Chen, Andrew R. Janowczyk, Matthew B. Palmer, Clarissa A. Cassol, Miroslav Sekulic, Jeffrey B. Hodgin, Jarcy Zee, Stephen M. Hewitt, John O’Toole, Paula Toro, John R. Sedor, Laura Barisoni, Anant Madabhushi, J. Sedor, K. Dell, M. Schachere, J. Negrey, K. Lemley, E. Lim, T. Srivastava, A. Garrett, C. Sethna, K. Laurent, G. Appel, M. Toledo, L. Barisoni, L. Greenbaum, C. Wang, C. Kang, S. Adler, C. Nast, J. LaPage, John H. Stroger, A. Athavale, M. Itteera, A. Neu, S. Boynton, F. Fervenza, M. Hogan, J. Lieske, V. Chernitskiy, F. Kaskel, N. Kumar, P. Flynn, J. Kopp, J. Blake, H. Trachtman, O. Zhdanova, F. Modersitzki, S. Vento, R. Lafayette, K. Mehta, C. Gadegbeku, D. Johnstone, S. Quinn-Boyle, D. Cattran, M. Hladunewich, H. Reich, P. Ling, M. Romano, A. Fornoni, C. Bidot, M. Kretzler, D. Gipson, A. Williams, J. LaVigne, V. Derebail, K. Gibson, A. Froment, S. Grubbs, L. Holzman, K. Meyers, K. Kallem, J. Lalli, K. Sambandam, Z. Wang, M. Rogers, A. Jefferson
Kidney International. 2021; 99(1): 86
[Pubmed]  [Google Scholar] [DOI]
85 Deep learning identified pathological abnormalities predictive of graft loss in kidney transplant biopsies
Zhengzi Yi, Fadi Salem, Madhav C. Menon, Karen Keung, Caixia Xi, Sebastian Hultin, M. Rizwan Haroon Al Rasheed, Li Li, Fei Su, Zeguo Sun, Chengguo Wei, Weiqing Huang, Samuel Fredericks, Qisheng Lin, Khadija Banu, Germaine Wong, Natasha M. Rogers, Samira Farouk, Paolo Cravedi, Meena Shingde, R. Neal Smith, Ivy A. Rosales, Philip J. O’Connell, Robert B. Colvin, Barbara Murphy, Weijia Zhang
Kidney International. 2021;
[Pubmed]  [Google Scholar] [DOI]
86 PAIP 2019: Liver cancer segmentation challenge
Yoo Jung Kim, Hyungjoon Jang, Kyoungbun Lee, Seongkeun Park, Sung-Gyu Min, Choyeon Hong, Jeong Hwan Park, Kanggeun Lee, Jisoo Kim, Wonjae Hong, Hyun Jung, Yanling Liu, Haran Rajkumar, Mahendra Khened, Ganapathy Krishnamurthi, Sen Yang, Xiyue Wang, Chang Hee Han, Jin Tae Kwak, Jianqiang Ma, Zhe Tang, Bahram Marami, Jack Zeineh, Zixu Zhao, Pheng-Ann Heng, Rüdiger Schmitz, Frederic Madesta, Thomas Rösch, Rene Werner, Jie Tian, Elodie Puybareau, Matteo Bovio, Xiufeng Zhang, Yifeng Zhu, Se Young Chun, Won-Ki Jeong, Peom Park, Jinwook Choi
Medical Image Analysis. 2021; 67: 101854
[Pubmed]  [Google Scholar] [DOI]
87 Residual cyclegan for robust domain transformation of histopathological tissue slides
Thomas de Bel, John-Melle Bokhorst, Jeroen van der Laak, Geert Litjens
Medical Image Analysis. 2021; 70: 102004
[Pubmed]  [Google Scholar] [DOI]
88 Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides
Abtin Riasatian, Morteza Babaie, Danial Maleki, Shivam Kalra, Mojtaba Valipour, Sobhan Hemati, Manit Zaveri, Amir Safarpoor, Sobhan Shafiei, Mehdi Afshari, Maral Rasoolijaberi, Milad Sikaroudi, Mohd Adnan, Sultaan Shah, Charles Choi, Savvas Damaskinos, Clinton JV Campbell, Phedias Diamandis, Liron Pantanowitz, Hany Kashani, Ali Ghodsi, H.R. Tizhoosh
Medical Image Analysis. 2021; 70: 102032
[Pubmed]  [Google Scholar] [DOI]
89 Fractal Neural Network: A new ensemble of fractal geometry and convolutional neural networks for the classification of histology images
Guilherme Freire Roberto, Alessandra Lumini, Leandro Alves Neves, Marcelo Zanchetta do Nascimento
Expert Systems with Applications. 2021; 166: 114103
[Pubmed]  [Google Scholar] [DOI]
90 Application of Single-Cell Approaches to Study Myeloproliferative Neoplasm Biology
Daniel Royston, Adam J. Mead, Bethan Psaila
Hematology/Oncology Clinics of North America. 2021; 35(2): 279
[Pubmed]  [Google Scholar] [DOI]
91 The role of machine learning in cardiovascular pathology
Carolyn Glass, Kyle J. Lafata, William Jeck, Roarke Horstmeyer, Colin Cooke, Jeffrey Everitt, Matthew Glass, David Dov, Michael A. Seidman
Canadian Journal of Cardiology. 2021;
[Pubmed]  [Google Scholar] [DOI]
92 A deep learning approach for mitosis detection: Application in tumor proliferation prediction from whole slide images
Ramin Nateghi, Habibollah Danyali, Mohammad Sadegh Helfroush
Artificial Intelligence in Medicine. 2021; 114: 102048
[Pubmed]  [Google Scholar] [DOI]
93 A hybrid deep learning approach for gland segmentation in prostate histopathological images
Massimo Salvi, Martino Bosco, Luca Molinaro, Alessandro Gambella, Mauro Papotti, U. Rajendra Acharya, Filippo Molinari
Artificial Intelligence in Medicine. 2021; 115: 102076
[Pubmed]  [Google Scholar] [DOI]
94 A financial statement fraud model based on synthesized attribute selection and a dataset with missing values and imbalanced classes
Ching-Hsue Cheng, Yung-Fu Kao, Hsien-Ping Lin
Applied Soft Computing. 2021; 108: 107487
[Pubmed]  [Google Scholar] [DOI]
95 Closing the translation gap: AI applications in digital pathology
David F. Steiner, Po-Hsuan Cameron Chen, Craig H. Mermel
Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 2021; 1875(1): 188452
[Pubmed]  [Google Scholar] [DOI]
96 A dataset and a methodology for intraoperative computer-aided diagnosis of a metastatic colon cancer in a liver
Dario Sitnik, Gorana Aralica, Mirko Hadžija, Marijana Popovic Hadžija, Arijana Pacic, Marija Milkovic Periša, Luka Manojlovic, Karolina Krstanac, Andrija Plavetic, Ivica Kopriva
Biomedical Signal Processing and Control. 2021; 66: 102402
[Pubmed]  [Google Scholar] [DOI]
97 Impact of stain normalization and patch selection on the performance of convolutional neural networks in histological breast and prostate cancer classification
Massimo Salvi, Filippo Molinari, U Rajendra Acharya, Luca Molinaro, Kristen M. Meiburger
Computer Methods and Programs in Biomedicine Update. 2021; 1: 100004
[Pubmed]  [Google Scholar] [DOI]
98 The impact of pre- and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis
Massimo Salvi, U. Rajendra Acharya, Filippo Molinari, Kristen M. Meiburger
Computers in Biology and Medicine. 2021; 128: 104129
[Pubmed]  [Google Scholar] [DOI]
99 Mitosis detection techniques in H&E stained breast cancer pathological images: A comprehensive review
Xipeng Pan, Yinghua Lu, Rushi Lan, Zhenbing Liu, Zujun Qin, Huadeng Wang, Zaiyi Liu
Computers & Electrical Engineering. 2021; 91: 107038
[Pubmed]  [Google Scholar] [DOI]
100 Deep learning powers cancer diagnosis in digital pathology
Yunjie He, Hong Zhao, Stephen T.C. Wong
Computerized Medical Imaging and Graphics. 2021; 88: 101820
[Pubmed]  [Google Scholar] [DOI]
101 PMNet: A probability map based scaled network for breast cancer diagnosis
Salman Ahmed, Maria Tariq, Hammad Naveed
Computerized Medical Imaging and Graphics. 2021; 89: 101863
[Pubmed]  [Google Scholar] [DOI]
102 A U-Net based framework to quantify glomerulosclerosis in digitized PAS and H&E stained human tissues
Jaime Gallego, Zaneta Swiderska-Chadaj, Tomasz Markiewicz, Michifumi Yamashita, M. Alejandra Gabaldon, Arkadiusz Gertych
Computerized Medical Imaging and Graphics. 2021; 89: 101865
[Pubmed]  [Google Scholar] [DOI]
103 A deep learning based multiscale approach to segment the areas of interest in whole slide images
Yanbo Feng, Adel Hafiane, Hélčne Laurent
Computerized Medical Imaging and Graphics. 2021; 90: 101923
[Pubmed]  [Google Scholar] [DOI]
104 Automated assessment of glomerulosclerosis and tubular atrophy using deep learning
Massimo Salvi, Alessandro Mogetta, Alessandro Gambella, Luca Molinaro, Antonella Barreca, Mauro Papotti, Filippo Molinari
Computerized Medical Imaging and Graphics. 2021; 90: 101930
[Pubmed]  [Google Scholar] [DOI]
105 A comprehensive survey of image segmentation: clustering methods, performance parameters, and benchmark datasets
Himanshu Mittal, Avinash Chandra Pandey, Mukesh Saraswat, Sumit Kumar, Raju Pal, Garv Modwel
Multimedia Tools and Applications. 2021;
[Pubmed]  [Google Scholar] [DOI]
106 Artificial intelligence applied to breast pathology
Mustafa Yousif, Paul J. van Diest, Arvydas Laurinavicius, David Rimm, Jeroen van der Laak, Anant Madabhushi, Stuart Schnitt, Liron Pantanowitz
Virchows Archiv. 2021;
[Pubmed]  [Google Scholar] [DOI]
107 In Situ Classification of Cell Types in Human Kidney Tissue Using 3D Nuclear Staining
Andre Woloshuk, Suraj Khochare, Aljohara F. Almulhim, Andrew T. McNutt, Dawson Dean, Daria Barwinska, Michael J. Ferkowicz, Michael T. Eadon, Katherine J. Kelly, Kenneth W. Dunn, Mohammad A. Hasan, Tarek M. El-Achkar, Seth Winfree
Cytometry Part A. 2021; 99(7): 707
[Pubmed]  [Google Scholar] [DOI]
108 Deep learning system for lymph node quantification and metastatic cancer identification from whole-slide pathology images
Yajie Hu, Feng Su, Kun Dong, Xinyu Wang, Xinya Zhao, Yumeng Jiang, Jianming Li, Jiafu Ji, Yu Sun
Gastric Cancer. 2021; 24(4): 868
[Pubmed]  [Google Scholar] [DOI]
109 Automated detection of COVID-19 using ensemble of transfer learning with deep convolutional neural network based on CT scans
Parisa gifani, Ahmad Shalbaf, Majid Vafaeezadeh
International Journal of Computer Assisted Radiology and Surgery. 2021; 16(1): 115
[Pubmed]  [Google Scholar] [DOI]
110 Breast Cancer Detection, Segmentation and Classification on Histopathology Images Analysis: A Systematic Review
R. Krithiga, P. Geetha
Archives of Computational Methods in Engineering. 2021; 28(4): 2607
[Pubmed]  [Google Scholar] [DOI]
111 A Comprehensive Review of Markov Random Field and Conditional Random Field Approaches in Pathology Image Analysis
Yixin Li, Chen Li, Xiaoyan Li, Kai Wang, Md Mamunur Rahaman, Changhao Sun, Hao Chen, Xinran Wu, Hong Zhang, Qian Wang
Archives of Computational Methods in Engineering. 2021;
[Pubmed]  [Google Scholar] [DOI]
112 A review on deep learning in medical image analysis
S. Suganyadevi, V. Seethalakshmi, K. Balasamy
International Journal of Multimedia Information Retrieval. 2021;
[Pubmed]  [Google Scholar] [DOI]
113 An optimal nuclei segmentation method based on enhanced multi-objective GWO
Ravi Sharma, Kapil Sharma
Complex & Intelligent Systems. 2021;
[Pubmed]  [Google Scholar] [DOI]
114 Generative Deep Learning in Digital Pathology Workflows
David Morrison, David Harris-Birtill, Peter D. Caie
The American Journal of Pathology. 2021; 191(10): 1717
[Pubmed]  [Google Scholar] [DOI]
115 Quantitative neurotoxicology: Potential role of artificial intelligence/deep learning approach
Anshul Srivastava, Joseph P. Hanig
Journal of Applied Toxicology. 2021; 41(7): 996
[Pubmed]  [Google Scholar] [DOI]
116 Quick Annotator: an open-source digital pathology based rapid image annotation tool
Runtian Miao, Robert Toth, Yu Zhou, Anant Madabhushi, Andrew Janowczyk
The Journal of Pathology: Clinical Research. 2021; 7(6): 542
[Pubmed]  [Google Scholar] [DOI]
117 Automated detection and delineation of hepatocellular carcinoma on multiphasic contrast-enhanced MRI using deep learning
Khaled Bousabarah, Brian Letzen, Jonathan Tefera, Lynn Savic, Isabel Schobert, Todd Schlachter, Lawrence H. Staib, Martin Kocher, Julius Chapiro, MingDe Lin
Abdominal Radiology. 2021; 46(1): 216
[Pubmed]  [Google Scholar] [DOI]
118 Cell Image Classification: A Comparative Overview
Mohammad Shifat-E-Rabbi, Xuwang Yin, Cailey E. Fitzgerald, Gustavo K. Rohde
Cytometry Part A. 2020; 97(4): 347
[Pubmed]  [Google Scholar] [DOI]
119 Computer-aided diagnosis in the era of deep learning
Heang-Ping Chan, Lubomir M. Hadjiiski, Ravi K. Samala
Medical Physics. 2020; 47(5)
[Pubmed]  [Google Scholar] [DOI]
120 A computer-aided diagnosis system for differentiation and delineation of malignant regions on whole-slide prostate histopathology image using spatial statistics and multidimensional DenseNet
Chiao-Min Chen, Yao-Sian Huang, Pei-Wei Fang, Cher-Wei Liang, Ruey-Feng Chang
Medical Physics. 2020; 47(3): 1021
[Pubmed]  [Google Scholar] [DOI]
121 Classification of digital pathological images of non-Hodgkin's lymphoma subtypes based on the fusion of transfer learning and principal component analysis
Jianfei Zhang, Wensheng Cui, Xiaoyan Guo, Bo Wang, Zhen Wang
Medical Physics. 2020; 47(9): 4241
[Pubmed]  [Google Scholar] [DOI]
122 A comparative study of breast cancer tumor classification by classical machine learning methods and deep learning method
Yadavendra, Satish Chand
Machine Vision and Applications. 2020; 31(6)
[Pubmed]  [Google Scholar] [DOI]
123 Culture codes of scientific concepts in global scientific online discourse
Dina I. Spicheva, Ekaterina V. Polyanskaya
AI & SOCIETY. 2020; 35(3): 699
[Pubmed]  [Google Scholar] [DOI]
124 Immune contexture analysis in immuno-oncology: applications and challenges of multiplex fluorescent immunohistochemistry
Reshma Shakya, Tam Hong Nguyen, Nigel Waterhouse, Rajiv Khanna
Clinical & Translational Immunology. 2020; 9(10)
[Pubmed]  [Google Scholar] [DOI]
125 Deep learning a boon for biophotonics?
Pranita Pradhan, Shuxia Guo, Oleg Ryabchykov, Juergen Popp, Thomas W. Bocklitz
Journal of Biophotonics. 2020; 13(6)
[Pubmed]  [Google Scholar] [DOI]
126 Autofocusing technologies for whole slide imaging and automated microscopy
Zichao Bian, Chengfei Guo, Shaowei Jiang, Jiakai Zhu, Ruihai Wang, Pengming Song, Zibang Zhang, Kazunori Hoshino, Guoan Zheng
Journal of Biophotonics. 2020; 13(12)
[Pubmed]  [Google Scholar] [DOI]
127 New methodologies in ageing research
Brenna Osborne, Daniela Bakula, Michael Ben Ezra, Charlotte Dresen, Esben Hartmann, Stella M. Kristensen, Garik V. Mkrtchyan, Malte H. Nielsen, Michael A. Petr, Morten Scheibye-Knudsen
Ageing Research Reviews. 2020; 62: 101094
[Pubmed]  [Google Scholar] [DOI]
128 Policy Implications of Artificial Intelligence and Machine Learning in Diabetes Management
David T. Broome, C. Beau Hilton, Neil Mehta
Current Diabetes Reports. 2020; 20(2)
[Pubmed]  [Google Scholar] [DOI]
129 Gated multimodal networks
John Arevalo, Thamar Solorio, Manuel Montes-y-Gómez, Fabio A. González
Neural Computing and Applications. 2020; 32(14): 10209
[Pubmed]  [Google Scholar] [DOI]
130 Novel convolutional neural network architecture for improved pulmonary nodule classification on computed tomography
Yi Wang, Hao Zhang, Kum Ju Chae, Younhee Choi, Gong Yong Jin, Seok-Bum Ko
Multidimensional Systems and Signal Processing. 2020; 31(3): 1163
[Pubmed]  [Google Scholar] [DOI]
131 A CNN-based active learning framework to identify mycobacteria in digitized Ziehl-Neelsen stained human tissues
Mu Yang, Karolina Nurzynska, Ann E. Walts, Arkadiusz Gertych
Computerized Medical Imaging and Graphics. 2020; 84: 101752
[Pubmed]  [Google Scholar] [DOI]
132 A machine learning model for detecting invasive ductal carcinoma with Google Cloud AutoML Vision
Yan Zeng, Jinmiao Zhang
Computers in Biology and Medicine. 2020; 122: 103861
[Pubmed]  [Google Scholar] [DOI]
133 Computer-aided classification of hepatocellular ballooning in liver biopsies from patients with NASH using persistent homology
Takashi Teramoto, Toshiya Shinohara, Akihiro Takiyama
Computer Methods and Programs in Biomedicine. 2020; 195: 105614
[Pubmed]  [Google Scholar] [DOI]
134 Classification of glomerular pathological findings using deep learning and nephrologist–AI collective intelligence approach
Eiichiro Uchino, Kanata Suzuki, Noriaki Sato, Ryosuke Kojima, Yoshinori Tamada, Shusuke Hiragi, Hideki Yokoi, Nobuhiro Yugami, Sachiko Minamiguchi, Hironori Haga, Motoko Yanagita, Yasushi Okuno
International Journal of Medical Informatics. 2020; 141: 104231
[Pubmed]  [Google Scholar] [DOI]
135 A bird’s-eye view of deep learning in bioimage analysis
Erik Meijering
Computational and Structural Biotechnology Journal. 2020; 18: 2312
[Pubmed]  [Google Scholar] [DOI]
136 Learning from irregularly sampled data for endomicroscopy super-resolution: a comparative study of sparse and dense approaches
Agnieszka Barbara Szczotka, Dzhoshkun Ismail Shakir, Daniele Ravě, Matthew J. Clarkson, Stephen P. Pereira, Tom Vercauteren
International Journal of Computer Assisted Radiology and Surgery. 2020; 15(7): 1167
[Pubmed]  [Google Scholar] [DOI]
137 Inconsistent Performance of Deep Learning Models on Mammogram Classification
Xiaoqin Wang, Gongbo Liang, Yu Zhang, Hunter Blanton, Zachary Bessinger, Nathan Jacobs
Journal of the American College of Radiology. 2020; 17(6): 796
[Pubmed]  [Google Scholar] [DOI]
138 Deep feature transfer learning for trusted and automated malware signature generation in private cloud environments
Daniel Nahmias, Aviad Cohen, Nir Nissim, Yuval Elovici
Neural Networks. 2020; 124: 243
[Pubmed]  [Google Scholar] [DOI]
139 An experimental study on classification of thyroid histopathology images using transfer learning
Vijaya Gajanan Buddhavarapu, Angel Arul Jothi J
Pattern Recognition Letters. 2020; 140: 1
[Pubmed]  [Google Scholar] [DOI]
140 Robust nuclei segmentation in histopathology using ASPPU-Net and boundary refinement
Tao Wan, Lei Zhao, Hongxiang Feng, Deyu Li, Chao Tong, Zengchang Qin
Neurocomputing. 2020; 408: 144
[Pubmed]  [Google Scholar] [DOI]
141 Review of the current state of digital image analysis in breast pathology
Martin C. Chang, Miralem Mrkonjic
The Breast Journal. 2020; 26(6): 1208
[Pubmed]  [Google Scholar] [DOI]
142 Computationally Derived Image Signature of Stromal Morphology Is Prognostic of Prostate Cancer Recurrence Following Prostatectomy in African American Patients
Hersh K. Bhargava, Patrick Leo, Robin Elliott, Andrew Janowczyk, Jon Whitney, Sanjay Gupta, Pingfu Fu, Kosj Yamoah, Francesca Khani, Brian D. Robinson, Timothy R. Rebbeck, Michael Feldman, Priti Lal, Anant Madabhushi
Clinical Cancer Research. 2020; 26(8): 1915
[Pubmed]  [Google Scholar] [DOI]
143 Deep Learning Algorithms for Corneal Amyloid Deposition Quantitation in Familial Amyloidosis
Klaus Kessel, Jaakko Mattila, Nina Linder, Tero Kivelä, Johan Lundin
Ocular Oncology and Pathology. 2020; 6(1): 58
[Pubmed]  [Google Scholar] [DOI]
144 Society of Toxicologic Pathology Digital Pathology and Image Analysis Special Interest Group Article*: Opinion on the Application of Artificial Intelligence and Machine Learning to Digital Toxicologic Pathology
Oliver C. Turner, Famke Aeffner, Dinesh S. Bangari, Wanda High, Brian Knight, Tom Forest, Brieuc Cossic, Lauren E. Himmel, Daniel G. Rudmann, Bhupinder Bawa, Anantharaman Muthuswamy, Olulanu H. Aina, Elijah F. Edmondson, Chandrassegar Saravanan, Danielle L. Brown, Tobias Sing, Manu M. Sebastian
Toxicologic Pathology. 2020; 48(2): 277
[Pubmed]  [Google Scholar] [DOI]
145 Artificial intelligence as the next step towards precision pathology
B. Acs, M. Rantalainen, J. Hartman
Journal of Internal Medicine. 2020; 288(1): 62
[Pubmed]  [Google Scholar] [DOI]
146 Impact of image analysis and artificial intelligence in thyroid pathology, with particular reference to cytological aspects
Ilaria Girolami, Stefano Marletta, Liron Pantanowitz, Evelin Torresani, Claudio Ghimenton, Mattia Barbareschi, Aldo Scarpa, Matteo Brunelli, Valeria Barresi, Pierpaolo Trimboli, Albino Eccher
Cytopathology. 2020; 31(5): 432
[Pubmed]  [Google Scholar] [DOI]
147 Same same but different: A Web-based deep learning application revealed classifying features for the histopathologic distinction of cortical malformations
Joshua Kubach, Angelika Muhlebner-Fahrngruber, Figen Soylemezoglu, Hajime Miyata, Pitt Niehusmann, Mrinalini Honavar, Fabio Rogerio, Se-Hoon Kim, Eleonora Aronica, Rita Garbelli, Samuel Vilz, Alexander Popp, Stefan Walcher, Christoph Neuner, Michael Scholz, Stefanie Kuerten, Verena Schropp, Sebastian Roeder, Philip Eichhorn, Markus Eckstein, Axel Brehmer, Katja Kobow, Roland Coras, Ingmar Blumcke, Samir Jabari
Epilepsia. 2020; 61(3): 421
[Pubmed]  [Google Scholar] [DOI]
148 A Multi-Organ Nucleus Segmentation Challenge
Neeraj Kumar, Ruchika Verma, Deepak Anand, Yanning Zhou, Omer Fahri Onder, Efstratios Tsougenis, Hao Chen, Pheng-Ann Heng, Jiahui Li, Zhiqiang Hu, Yunzhi Wang, Navid Alemi Koohbanani, Mostafa Jahanifar, Neda Zamani Tajeddin, Ali Gooya, Nasir Rajpoot, Xuhua Ren, Sihang Zhou, Qian Wang, Dinggang Shen, Cheng-Kun Yang, Chi-Hung Weng, Wei-Hsiang Yu, Chao-Yuan Yeh, Shuang Yang, Shuoyu Xu, Pak Hei Yeung, Peng Sun, Amirreza Mahbod, Gerald Schaefer, Isabella Ellinger, Rupert Ecker, Orjan Smedby, Chunliang Wang, Benjamin Chidester, That-Vinh Ton, Minh-Triet Tran, Jian Ma, Minh N. Do, Simon Graham, Quoc Dang Vu, Jin Tae Kwak, Akshaykumar Gunda, Raviteja Chunduri, Corey Hu, Xiaoyang Zhou, Dariush Lotfi, Reza Safdari, Antanas Kascenas, Alison O'Neil, Dennis Eschweiler, Johannes Stegmaier, Yanping Cui, Baocai Yin, Kailin Chen, Xinmei Tian, Philipp Gruening, Erhardt Barth, Elad Arbel, Itay Remer, Amir Ben-Dor, Ekaterina Sirazitdinova, Matthias Kohl, Stefan Braunewell, Yuexiang Li, Xinpeng Xie, Linlin
IEEE Transactions on Medical Imaging. 2020; 39(5): 1380
[Pubmed]  [Google Scholar] [DOI]
149 Guided Soft Attention Network for Classification of Breast Cancer Histopathology Images
Heechan Yang, Ji-Ye Kim, Hyongsuk Kim, Shyam P. Adhikari
IEEE Transactions on Medical Imaging. 2020; 39(5): 1306
[Pubmed]  [Google Scholar] [DOI]
150 Multiplex Cellular Communities in Multi-Gigapixel Colorectal Cancer Histology Images for Tissue Phenotyping
Sajid Javed, Arif Mahmood, Naoufel Werghi, Ksenija Benes, Nasir Rajpoot
IEEE Transactions on Image Processing. 2020; 29: 9204
[Pubmed]  [Google Scholar] [DOI]
151 Improved small blob detection in 3D images using jointly constrained deep learning and Hessian analysis
Yanzhe Xu, Teresa Wu, Fei Gao, Jennifer R. Charlton, Kevin M. Bennett
Scientific Reports. 2020; 10(1)
[Pubmed]  [Google Scholar] [DOI]
152 Tailored for Real-World: A Whole Slide Image Classification System Validated on Uncurated Multi-Site Data Emulating the Prospective Pathology Workload
Julianna D. Ianni, Rajath E. Soans, Sivaramakrishnan Sankarapandian, Ramachandra Vikas Chamarthi, Devi Ayyagari, Thomas G. Olsen, Michael J. Bonham, Coleman C. Stavish, Kiran Motaparthi, Clay J. Cockerell, Theresa A. Feeser, Jason B. Lee
Scientific Reports. 2020; 10(1)
[Pubmed]  [Google Scholar] [DOI]
153 Automated Classification for Visual-Only Postmortem Inspection of Porcine Pathology
Stephen McKenna, Telmo Amaral, Ilias Kyriazakis
IEEE Transactions on Automation Science and Engineering. 2020; 17(2): 1005
[Pubmed]  [Google Scholar] [DOI]
154 Computer-Aided Diagnosis in Histopathological Images of the Endometrium Using a Convolutional Neural Network and Attention Mechanisms
Hao Sun, Xianxu Zeng, Tao Xu, Gang Peng, Yutao Ma
IEEE Journal of Biomedical and Health Informatics. 2020; 24(6): 1664
[Pubmed]  [Google Scholar] [DOI]
155 AI in Medical Imaging Informatics: Current Challenges and Future Directions
Andreas S. Panayides, Amir Amini, Nenad D. Filipovic, Ashish Sharma, Sotirios A. Tsaftaris, Alistair Young, David Foran, Nhan Do, Spyretta Golemati, Tahsin Kurc, Kun Huang, Konstantina S. Nikita, Ben P. Veasey, Michalis Zervakis, Joel H. Saltz, Constantinos S. Pattichis
IEEE Journal of Biomedical and Health Informatics. 2020; 24(7): 1837
[Pubmed]  [Google Scholar] [DOI]
156 Proteomic investigations into resistance in colorectal cancer
David I. Cantor, Harish R. Cheruku, Jack Westacott, Joo-Shik Shin, Abidali Mohamedali, Seong Boem Ahn
Expert Review of Proteomics. 2020; 17(1): 49
[Pubmed]  [Google Scholar] [DOI]
157 Supervised machine learning tools: a tutorial for clinicians
Lucas Lo Vercio, Kimberly Amador, Jordan J Bannister, Sebastian Crites, Alejandro Gutierrez, M. Ethan MacDonald, Jasmine Moore, Pauline Mouches, Deepthi Rajashekar, Serena Schimert, Nagesh Subbanna, Anup Tuladhar, Nanjia Wang, Matthias Wilms, Anthony Winder, Nils D Forkert
Journal of Neural Engineering. 2020; 17(6): 062001
[Pubmed]  [Google Scholar] [DOI]
158 Artificial intelligence driven next-generation renal histomorphometry
Briana A. Santo, Avi Z. Rosenberg, Pinaki Sarder
Current Opinion in Nephrology and Hypertension. 2020; 29(3): 265
[Pubmed]  [Google Scholar] [DOI]
159 MitosisNet: End-to-End Mitotic Cell Detection by Multi-Task Learning
Md Zahangir Alom, Theus Aspiras, Tarek M. Taha, T.J. Bowen, Vijayan K. Asari
IEEE Access. 2020; 8: 68695
[Pubmed]  [Google Scholar] [DOI]
160 An Accurate and Fast Cardio-Views Classification System Based on Fused Deep Features and LSTM
Ahmed I. Shahin, Sultan Almotairi
IEEE Access. 2020; 8: 135184
[Pubmed]  [Google Scholar] [DOI]
161 Pan-cancer diagnostic consensus through searching archival histopathology images using artificial intelligence
Shivam Kalra, H. R. Tizhoosh, Sultaan Shah, Charles Choi, Savvas Damaskinos, Amir Safarpoor, Sobhan Shafiei, Morteza Babaie, Phedias Diamandis, Clinton J. V. Campbell, Liron Pantanowitz
npj Digital Medicine. 2020; 3(1)
[Pubmed]  [Google Scholar] [DOI]
162 Accurate diagnosis of lymphoma on whole-slide histopathology images using deep learning
Charlotte Syrykh, Arnaud Abreu, Nadia Amara, Aurore Siegfried, Véronique Maisongrosse, François X. Frenois, Laurent Martin, Cédric Rossi, Camille Laurent, Pierre Brousset
npj Digital Medicine. 2020; 3(1)
[Pubmed]  [Google Scholar] [DOI]
163 Non-disruptive collagen characterization in clinical histopathology using cross-modality image synthesis
Adib Keikhosravi, Bin Li, Yuming Liu, Matthew W. Conklin, Agnes G. Loeffler, Kevin W. Eliceiri
Communications Biology. 2020; 3(1)
[Pubmed]  [Google Scholar] [DOI]
164 Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning
Zhigang Song, Shuangmei Zou, Weixun Zhou, Yong Huang, Liwei Shao, Jing Yuan, Xiangnan Gou, Wei Jin, Zhanbo Wang, Xin Chen, Xiaohui Ding, Jinhong Liu, Chunkai Yu, Calvin Ku, Cancheng Liu, Zhuo Sun, Gang Xu, Yuefeng Wang, Xiaoqing Zhang, Dandan Wang, Shuhao Wang, Wei Xu, Richard C. Davis, Huaiyin Shi
Nature Communications. 2020; 11(1)
[Pubmed]  [Google Scholar] [DOI]
165 Deep learning shows the capability of high-level computer-aided diagnosis in malignant lymphoma
Hiroaki Miyoshi, Kensaku Sato, Yoshinori Kabeya, Sho Yonezawa, Hiroki Nakano, Yusuke Takeuchi, Issei Ozawa, Shoichi Higo, Eriko Yanagida, Kyohei Yamada, Kei Kohno, Takuya Furuta, Hiroko Muta, Mai Takeuchi, Yuya Sasaki, Takuro Yoshimura, Kotaro Matsuda, Reiji Muto, Mayuko Moritsubo, Kanako Inoue, Takaharu Suzuki, Hiroaki Sekinaga, Koichi Ohshima
Laboratory Investigation. 2020; 100(10): 1300
[Pubmed]  [Google Scholar] [DOI]
166 Automated detection algorithm for C4d immunostaining showed comparable diagnostic performance to pathologists in renal allograft biopsy
Gyuheon Choi, Young-Gon Kim, Haeyon Cho, Namkug Kim, Hyunna Lee, Kyung Chul Moon, Heounjeong Go
Modern Pathology. 2020; 33(8): 1626
[Pubmed]  [Google Scholar] [DOI]
167 Deep-Hipo: Multi-scale receptive field deep learning for histopathological image analysis
Sai Chandra Kosaraju, Jie Hao, Hyun Min Koh, Mingon Kang
Methods. 2020; 179: 3
[Pubmed]  [Google Scholar] [DOI]
168 Deep-learning approaches for Gleason grading of prostate biopsies
Anant Madabhushi, Michael D Feldman, Patrick Leo
The Lancet Oncology. 2020; 21(2): 187
[Pubmed]  [Google Scholar] [DOI]
169 Clinical deployment of AI for prostate cancer diagnosis
Andrew Janowczyk, Patrick Leo, Mark A Rubin
The Lancet Digital Health. 2020; 2(8): e383
[Pubmed]  [Google Scholar] [DOI]
170 Dataset of segmented nuclei in hematoxylin and eosin stained histopathology images of ten cancer types
Le Hou, Rajarsi Gupta, John S. Van Arnam, Yuwei Zhang, Kaustubh Sivalenka, Dimitris Samaras, Tahsin M. Kurc, Joel H. Saltz
Scientific Data. 2020; 7(1)
[Pubmed]  [Google Scholar] [DOI]
171 Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group
Mohamed Amgad, Elisabeth Specht Stovgaard, Eva Balslev, Jeppe Thagaard, Weijie Chen, Sarah Dudgeon, Ashish Sharma, Jennifer K. Kerner, Carsten Denkert, Yinyin Yuan, Khalid AbdulJabbar, Stephan Wienert, Peter Savas, Leonie Voorwerk, Andrew H. Beck, Anant Madabhushi, Johan Hartman, Manu M. Sebastian, Hugo M. Horlings, Jan Hudecek, Francesco Ciompi, David A. Moore, Rajendra Singh, Elvire Roblin, Marcelo Luiz Balancin, Marie-Christine Mathieu, Jochen K. Lennerz, Pawan Kirtani, I-Chun Chen, Jeremy P. Braybrooke, Giancarlo Pruneri, Sandra Demaria, Sylvia Adams, Stuart J. Schnitt, Sunil R. Lakhani, Federico Rojo, Laura Comerma, Sunil S. Badve, Mehrnoush Khojasteh, W. Fraser Symmans, Christos Sotiriou, Paula Gonzalez-Ericsson, Katherine L. Pogue-Geile, Rim S. Kim, David L. Rimm, Giuseppe Viale, Stephen M. Hewitt, John M. S. Bartlett, Frédérique Penault-Llorca, Shom Goel, Huang-Chun Lien, Sibylle Loibl, Zuzana Kos, Sherene Loi, Matthew G. Hanna, Stefan Michiels, Marleen Kok, Torsten O. Nielsen,
npj Breast Cancer. 2020; 6(1)
[Pubmed]  [Google Scholar] [DOI]
172 Cellular community detection for tissue phenotyping in colorectal cancer histology images
Sajid Javed, Arif Mahmood, Muhammad Moazam Fraz, Navid Alemi Koohbanani, Ksenija Benes, Yee-Wah Tsang, Katherine Hewitt, David Epstein, David Snead, Nasir Rajpoot
Medical Image Analysis. 2020; 63: 101696
[Pubmed]  [Google Scholar] [DOI]
173 Diagnosing Epidermal basal Squamous Cell Carcinoma in High-resolution, and Poorly Labeled Histopathological Imaging
Mani Manavalan
Engineering International. 2020; 8(2): 139
[Pubmed]  [Google Scholar] [DOI]
174 A deep learning image-based intrinsic molecular subtype classifier of breast tumors reveals tumor heterogeneity that may affect survival
Mustafa I. Jaber, Bing Song, Clive Taylor, Charles J. Vaske, Stephen C. Benz, Shahrooz Rabizadeh, Patrick Soon-Shiong, Christopher W. Szeto
Breast Cancer Research. 2020; 22(1)
[Pubmed]  [Google Scholar] [DOI]
175 Validation of machine learning models to detect amyloid pathologies across institutions
Juan C. Vizcarra, Marla Gearing, Michael J. Keiser, Jonathan D. Glass, Brittany N. Dugger, David A. Gutman
Acta Neuropathologica Communications. 2020; 8(1)
[Pubmed]  [Google Scholar] [DOI]
176 Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis
Yijiang Chen, Andrew Janowczyk, Anant Madabhushi
JCO Clinical Cancer Informatics. 2020; (4): 221
[Pubmed]  [Google Scholar] [DOI]
177 Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data
Zixiao Lu, Siwen Xu, Wei Shao, Yi Wu, Jie Zhang, Zhi Han, Qianjin Feng, Kun Huang
JCO Clinical Cancer Informatics. 2020; (4): 480
[Pubmed]  [Google Scholar] [DOI]
178 Reimagining T Staging Through Artificial Intelligence and Machine Learning Image Processing Approaches in Digital Pathology
Kaustav Bera, Ian Katz, Anant Madabhushi
JCO Clinical Cancer Informatics. 2020; (4): 1039
[Pubmed]  [Google Scholar] [DOI]
179 Hybrid autofluorescence and photoacoustic label-free microscopy for the investigation and identification of malignancies in ocular biopsies
George J. Tserevelakis, Kostas G. Mavrakis, Danai Pantazopoulou, Eleni Lagoudaki, Efstathios Detorakis, Giannis Zacharakis
Optics Letters. 2020; 45(20): 5748
[Pubmed]  [Google Scholar] [DOI]
180 Bioinformatics analysis of whole slide images reveals significant neighborhood preferences of tumor cells in Hodgkin lymphoma
Jennifer Hannig, Hendrik Schäfer, Jörg Ackermann, Marie Hebel, Tim Schäfer, Claudia Döring, Sylvia Hartmann, Martin-Leo Hansmann, Ina Koch, Jason A. Papin
PLOS Computational Biology. 2020; 16(1): e1007516
[Pubmed]  [Google Scholar] [DOI]
181 Glioma Grading via Analysis of Digital Pathology Images Using Machine Learning
Saima Rathore, Tamim Niazi, Muhammad Aksam Iftikhar, Ahmad Chaddad
Cancers. 2020; 12(3): 578
[Pubmed]  [Google Scholar] [DOI]
182 Artificial Intelligence and Digital Microscopy Applications in Diagnostic Hematopathology
Hanadi El El Achi, Joseph D. Khoury
Cancers. 2020; 12(4): 797
[Pubmed]  [Google Scholar] [DOI]
183 Integrative Data Augmentation with U-Net Segmentation Masks Improves Detection of Lymph Node Metastases in Breast Cancer Patients
Yong Won Jin, Shuo Jia, Ahmed Bilal Ashraf, Pingzhao Hu
Cancers. 2020; 12(10): 2934
[Pubmed]  [Google Scholar] [DOI]
184 Enhancing Multi-tissue and Multi-scale Cell Nuclei Segmentation with Deep Metric Learning
Tomas Iesmantas, Agne Paulauskaite-Taraseviciene, Kristina Sutiene
Applied Sciences. 2020; 10(2): 615
[Pubmed]  [Google Scholar] [DOI]
185 An Empirical Evaluation of Nuclei Segmentation from H&E Images in a Real Application Scenario
Lorenzo Putzu, Giorgio Fumera
Applied Sciences. 2020; 10(22): 7982
[Pubmed]  [Google Scholar] [DOI]
186 Application of Big Data Technology for COVID-19 Prevention and Control in China: Lessons and Recommendations
Jun Wu, Jian Wang, Stephen Nicholas, Elizabeth Maitland, Qiuyan Fan
Journal of Medical Internet Research. 2020; 22(10): e21980
[Pubmed]  [Google Scholar] [DOI]
187 Automated histologic diagnosis of CNS tumors with machine learning
Siri Sahib S Khalsa, Todd C Hollon, Arjun Adapa, Esteban Urias, Sudharsan Srinivasan, Neil Jairath, Julianne Szczepanski, Peter Ouillette, Sandra Camelo-Piragua, Daniel A Orringer
CNS Oncology. 2020; 9(2): CNS56
[Pubmed]  [Google Scholar] [DOI]
188 The Utility of Deep Learning in Breast Ultrasonic Imaging: A Review
Tomoyuki Fujioka, Mio Mori, Kazunori Kubota, Jun Oyama, Emi Yamaga, Yuka Yashima, Leona Katsuta, Kyoko Nomura, Miyako Nara, Goshi Oda, Tsuyoshi Nakagawa, Yoshio Kitazume, Ukihide Tateishi
Diagnostics. 2020; 10(12): 1055
[Pubmed]  [Google Scholar] [DOI]
189 Artificial Intelligence Tools for Refining Lung Cancer Screening
J. Luis Espinoza, Le Thanh Dong
Journal of Clinical Medicine. 2020; 9(12): 3860
[Pubmed]  [Google Scholar] [DOI]
190 Time Series Analysis and Forecasting with Automated Machine Learning on a National ICD-10 Database
Victor Olsavszky, Mihnea Dosius, Cristian Vladescu, Johannes Benecke
International Journal of Environmental Research and Public Health. 2020; 17(14): 4979
[Pubmed]  [Google Scholar] [DOI]
191 Arctic Vision: Using Neural Networks for Ice Object Classification, and Controlling How They Fail
Ole-Magnus Pedersen, Ekaterina Kim
Journal of Marine Science and Engineering. 2020; 8(10): 770
[Pubmed]  [Google Scholar] [DOI]
192 Objective Diagnosis for Histopathological Images Based on Machine Learning Techniques: Classical Approaches and New Trends
Naira Elazab, Hassan Soliman, Shaker El-Sappagh, S. M. Riazul Islam, Mohammed Elmogy
Mathematics. 2020; 8(11): 1863
[Pubmed]  [Google Scholar] [DOI]
193 Relevant Applications of Generative Adversarial Networks in Drug Design and Discovery: Molecular De Novo Design, Dimensionality Reduction, and De Novo Peptide and Protein Design
Eugene Lin, Chieh-Hsin Lin, Hsien-Yuan Lane
Molecules. 2020; 25(14): 3250
[Pubmed]  [Google Scholar] [DOI]
194 Feasibility of fully automated classification of whole slide images based on deep learning
Kyung-Ok Cho, Sung Hak Lee, Hyun-Jong Jang
The Korean Journal of Physiology & Pharmacology. 2020; 24(1): 89
[Pubmed]  [Google Scholar] [DOI]
195 Classification of Molecular Biomarkers
Ankeet Shah, Dominic C Grimberg, Brant A Inman
Société Internationale d’Urologie Journal. 2020; 1(1): 8
[Pubmed]  [Google Scholar] [DOI]
196 Clinical Decision Support for Ovarian Carcinoma Subtype Classification: A Pilot Observer Study With Pathology Trainees
Marios A. Gavrielides, Meghan Miller, Ian S. Hagemann, Heba Abdelal, Zahra Alipour, Jie-Fu Chen, Behzad Salari, Lulu Sun, Huifang Zhou, Jeffrey D Seidman
Archives of Pathology & Laboratory Medicine. 2020; 144(7): 869
[Pubmed]  [Google Scholar] [DOI]
197 Counting Mitoses With Digital Pathology in Breast Phyllodes Tumors
Zi Long Chow, Aye Aye Thike, Hui Hua Li, Nur Diyana Md Nasir, Joe Poh Sheng Yeong, Puay Hoon Tan
Archives of Pathology & Laboratory Medicine. 2020; 144(11): 1397
[Pubmed]  [Google Scholar] [DOI]
198 Deep learning techniques for detecting preneoplastic and neoplastic lesions in human colorectal histological images
Paola Sena, Rita Fioresi, Francesco Faglioni, Lorena Losi, Giovanni Faglioni, Luca Roncucci
Oncology Letters. 2019;
[Pubmed]  [Google Scholar] [DOI]
199 The Impact of Artificial Intelligence on the Labor Market
Michael Webb
SSRN Electronic Journal. 2019;
[Pubmed]  [Google Scholar] [DOI]
200 Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics
Zhichao Liu, Erika P. Portero, Yiren Jian, Yunjie Zhao, Rosemary M. Onjiko, Chen Zeng, Peter Nemes
Analytical Chemistry. 2019; 91(9): 5768
[Pubmed]  [Google Scholar] [DOI]
201 Classification of Benign and Malignant Breast Cancer using Supervised Machine Learning Algorithms Based on Image and Numeric Datasets
Ratula Ray, Azian Azamimi Abdullah, Debasish Kumar Mallick, Satya Ranjan Dash
Journal of Physics: Conference Series. 2019; 1372(1): 012062
[Pubmed]  [Google Scholar] [DOI]
202 Spatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non–Small Cell Lung Cancer
Germán Corredor, Xiangxue Wang, Yu Zhou, Cheng Lu, Pingfu Fu, Konstantinos Syrigos, David L. Rimm, Michael Yang, Eduardo Romero, Kurt A. Schalper, Vamsidhar Velcheti, Anant Madabhushi
Clinical Cancer Research. 2019; 25(5): 1526
[Pubmed]  [Google Scholar] [DOI]
203 Automating the Paris System for urine cytopathology—A hybrid deep-learning and morphometric approach
Louis J. Vaickus, Arief A. Suriawinata, Jason W. Wei, Xiaoying Liu
Cancer Cytopathology. 2019; 127(2): 98
[Pubmed]  [Google Scholar] [DOI]
204 Performance of an artificial intelligence algorithm for reporting urine cytopathology
Adit B. Sanghvi, Erastus Z. Allen, Keith M. Callenberg, Liron Pantanowitz
Cancer Cytopathology. 2019; 127(10): 658
[Pubmed]  [Google Scholar] [DOI]
205 Advances in the computational and molecular understanding of the prostate cancer cell nucleus
Neil M. Carleton, George Lee, Anant Madabhushi, Robert W. Veltri
Journal of Cellular Biochemistry. 2018; 119(9): 7127
[Pubmed]  [Google Scholar] [DOI]
206 Cell detection in pathology and microscopy images with multi-scale fully convolutional neural networks
Xipeng Pan,Dengxian Yang,Lingqiao Li,Zhenbing Liu,Huihua Yang,Zhiwei Cao,Yubei He,Zhen Ma,Yiyi Chen
World Wide Web. 2018;
[Pubmed]  [Google Scholar] [DOI]
207 Association of Pathological Fibrosis With Renal Survival Using Deep Neural Networks
Vijaya B. Kolachalama,Priyamvada Singh,Christopher Q. Lin,Dan Mun,Mostafa E. Belghasem,Joel M. Henderson,Jean M. Francis,David J. Salant,Vipul C. Chitalia
Kidney International Reports. 2018;
[Pubmed]  [Google Scholar] [DOI]
208 COUNTERPOINT: Is International Statistical Classification of Diseases and Related Health Problems, 10th Revision Diagnosis Coding Important in the Era of Big Data? No
David M. Liebovitz,John Fahrenbach
Chest. 2018;
[Pubmed]  [Google Scholar] [DOI]
209 Machine Learning Methods for Histopathological Image Analysis
Daisuke Komura,Shumpei Ishikawa
Computational and Structural Biotechnology Journal. 2018; 16: 34
[Pubmed]  [Google Scholar] [DOI]
210 Deep learning based tissue analysis predicts outcome in colorectal cancer
Dmitrii Bychkov,Nina Linder,Riku Turkki,Stig Nordling,Panu E. Kovanen,Clare Verrill,Margarita Walliander,Mikael Lundin,Caj Haglund,Johan Lundin
Scientific Reports. 2018; 8(1)
[Pubmed]  [Google Scholar] [DOI]
211 Automatic labeling of molecular biomarkers of immunohistochemistry images using fully convolutional networks
Fahime Sheikhzadeh,Rabab K. Ward,Dirk van Niekerk,Martial Guillaud,Christophe Egles
PLOS ONE. 2018; 13(1): e0190783
[Pubmed]  [Google Scholar] [DOI]
212 Application of deep learning to the classification of images from colposcopy
Masakazu Sato, Koji Horie, Aki Hara, Yuichiro Miyamoto, Kazuko Kurihara, Kensuke Tomio, Harushige Yokota
Oncology Letters. 2018;
[Pubmed]  [Google Scholar] [DOI]
213 Glomerulus Classification and Detection Based on Convolutional Neural Networks
Jaime Gallego,Anibal Pedraza,Samuel Lopez,Georg Steiner,Lucia Gonzalez,Arvydas Laurinavicius,Gloria Bueno
Journal of Imaging. 2018; 4(1): 20
[Pubmed]  [Google Scholar] [DOI]
214 Systems biology primer: the basic methods and approaches
Iman Tavassoly, Joseph Goldfarb, Ravi Iyengar
Essays in Biochemistry. 2018; 62(4): 487
[Pubmed]  [Google Scholar] [DOI]
215 Very Deep Convolutional Neural Networks for Morphologic Classification of Erythrocytes
Thomas J S Durant, Eben M Olson, Wade L Schulz, Richard Torres
Clinical Chemistry. 2017; 63(12): 1847
[Pubmed]  [Google Scholar] [DOI]
216 Deep Learning Makes Its Way to the Clinical Laboratory
Ronald Jackups
Clinical Chemistry. 2017; 63(12): 1790
[Pubmed]  [Google Scholar] [DOI]
217 A novel machine learning approach reveals latent vascular phenotypes predictive of renal cancer outcome
Nathan Ing,Fangjin Huang,Andrew Conley,Sungyong You,Zhaoxuan Ma,Sergey Klimov,Chisato Ohe,Xiaopu Yuan,Mahul B. Amin,Robert Figlin,Arkadiusz Gertych,Beatrice S. Knudsen
Scientific Reports. 2017; 7(1)
[Pubmed]  [Google Scholar] [DOI]
218 Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images
Xiangxue Wang,Andrew Janowczyk,Yu Zhou,Rajat Thawani,Pingfu Fu,Kurt Schalper,Vamsidhar Velcheti,Anant Madabhushi
Scientific Reports. 2017; 7(1)
[Pubmed]  [Google Scholar] [DOI]
219 Glandular Morphometrics for Objective Grading of Colorectal Adenocarcinoma Histology Images
Ruqayya Awan,Korsuk Sirinukunwattana,David Epstein,Samuel Jefferyes,Uvais Qidwai,Zia Aftab,Imaad Mujeeb,David Snead,Nasir Rajpoot
Scientific Reports. 2017; 7(1)
[Pubmed]  [Google Scholar] [DOI]
220 Prediction of multi-drug resistant TB from CT pulmonary Images based on deep learning techniques
Xiaohong Gao,Yu Qian
Molecular Pharmaceutics. 2017;
[Pubmed]  [Google Scholar] [DOI]
221 Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer
Michel E. Vandenberghe,Marietta L. J. Scott,Paul W. Scorer,Magnus Söderberg,Denis Balcerzak,Craig Barker
Scientific Reports. 2017; 7: 45938
[Pubmed]  [Google Scholar] [DOI]
222 Precision histology: how deep learning is poised to revitalize histomorphology for personalized cancer care
Ugljesa Djuric,Gelareh Zadeh,Kenneth Aldape,Phedias Diamandis
npj Precision Oncology. 2017; 1(1)
[Pubmed]  [Google Scholar] [DOI]
223 Retrieval From and Understanding of Large-Scale Multi-modal Medical Datasets: A Review
Henning Muller,Devrim Unay
IEEE Transactions on Multimedia. 2017; 19(9): 2093
[Pubmed]  [Google Scholar] [DOI]
224 Automatic Nuclear Segmentation Using Multiscale Radial Line Scanning With Dynamic Programming
Hongming Xu,Cheng Lu,Richard Berendt,Naresh Jha,Mrinal Mandal
IEEE Transactions on Biomedical Engineering. 2017; 64(10): 2475
[Pubmed]  [Google Scholar] [DOI]
225 A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology
Neeraj Kumar,Ruchika Verma,Sanuj Sharma,Surabhi Bhargava,Abhishek Vahadane,Amit Sethi
IEEE Transactions on Medical Imaging. 2017; 36(7): 1550
[Pubmed]  [Google Scholar] [DOI]
226 Enabling Precision Cardiology Through Multiscale Biology and Systems Medicine
Kipp W. Johnson,Khader Shameer,Benjamin S. Glicksberg,Ben Readhead,Partho P. Sengupta,Johan L.M. Björkegren,Jason C. Kovacic,Joel T. Dudley
JACC: Basic to Translational Science. 2017; 2(3): 311
[Pubmed]  [Google Scholar] [DOI]
227 A survey on deep learning in medical image analysis
Geert Litjens,Thijs Kooi,Babak Ehteshami Bejnordi,Arnaud Arindra Adiyoso Setio,Francesco Ciompi,Mohsen Ghafoorian,Jeroen A.W.M. van der Laak,Bram van Ginneken,Clara I. Sánchez
Medical Image Analysis. 2017; 42: 60
[Pubmed]  [Google Scholar] [DOI]
228 A deep learning method for classifying mammographic breast density categories
Aly A. Mohamed,Wendie A. Berg,Hong Peng,Yahong Luo,Rachel C. Jankowitz,Shandong Wu
Medical Physics. 2017;
[Pubmed]  [Google Scholar] [DOI]
229 A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers
David Romo-Bucheli,Andrew Janowczyk,Hannah Gilmore,Eduardo Romero,Anant Madabhushi
Cytometry Part A. 2017;
[Pubmed]  [Google Scholar] [DOI]
230 Automatic cellularity assessment from post-treated breast surgical specimens
Mohammad Peikari,Sherine Salama,Sharon Nofech-Mozes,Anne L. Martel
Cytometry Part A. 2017;
[Pubmed]  [Google Scholar] [DOI]
231 Bringing 3D tumor models to the clinic - predictive value for personalized medicine
Kathrin Halfter,Barbara Mayer
Biotechnology Journal. 2017; : 1600295
[Pubmed]  [Google Scholar] [DOI]
232 Development of CD3 cell quantitation algorithms for renal allograft biopsy rejection assessment utilizing open source image analysis software
Andres Moon,Geoffrey H. Smith,Jun Kong,Thomas E. Rogers,Carla L. Ellis,Alton B. “Brad” Farris
Virchows Archiv. 2017;
[Pubmed]  [Google Scholar] [DOI]

 

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