| 1 |
Deep learning-based automated mitosis detection in histopathology images for breast cancer grading |
|
|
| Tojo Mathew, B. Ajith, Jyoti R. Kini, Jeny Rajan |
|
| International Journal of Imaging Systems and Technology. 2022; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 2 |
Novel architecture with selected feature vector for effective classification of mitotic and non-mitotic cells in breast cancer histology images |
|
|
| Mobeen Ur Rehman, Suhail Akhtar, Muhammad Zakwan, Muhammad Habib Mahmood |
|
| Biomedical Signal Processing and Control. 2022; 71: 103212 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 3 |
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] |
|
| 4 |
Computer-Aided Assessment of Melanocytic Lesions by Means of a Mitosis Algorithm |
|
|
| Bart Sturm, David Creytens, Jan Smits, Ariadne H. A. G. Ooms, Erik Eijken, Eline Kurpershoek, Heidi V. N. Küsters-Vandevelde, Carla Wauters, Willeke A. M. Blokx, Jeroen A. W. M. van der Laak |
|
| Diagnostics. 2022; 12(2): 436 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 5 |
Machine Learning Methods for Histopathological Image Analysis: A Review |
|
|
| Jonathan de Matos, Steve Ataky, Alceu de Souza Britto, Luiz Soares de Oliveira, Alessandro Lameiras Koerich |
|
| Electronics. 2021; 10(5): 562 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 6 |
Evaluating Cancer-Related Biomarkers Based on Pathological Images: A Systematic Review |
|
|
| Xiaoliang Xie, Xulin Wang, Yuebin Liang, Jingya Yang, Yan Wu, Li Li, Xin Sun, Pingping Bing, Binsheng He, Geng Tian, Xiaoli Shi |
|
| Frontiers in Oncology. 2021; 11 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 7 |
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] |
|
| 8 |
An investigation of XGBoost-based algorithm for breast cancer classification |
|
|
| Xin Yu Liew, Nazia Hameed, Jeremie Clos |
|
| Machine Learning with Applications. 2021; 6: 100154 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 9 |
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] |
|
| 10 |
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] |
|
| 11 |
Machine learning techniques for mitoses classification |
|
|
| Shima Nofallah, Sachin Mehta, Ezgi Mercan, Stevan Knezevich, Caitlin J. May, Donald Weaver, Daniela Witten, Joann G. Elmore, Linda Shapiro |
|
| Computerized Medical Imaging and Graphics. 2021; 87: 101832 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 12 |
A review on image-based approaches for breast cancer detection, segmentation, and classification |
|
|
| Zahra Rezaei |
|
| Expert Systems with Applications. 2021; 182: 115204 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 13 |
An explainable ensemble feedforward method with Gaussian convolutional filter |
|
|
| Jingchen Li, Haobin Shi, Kao-Shing Hwang |
|
| Knowledge-Based Systems. 2021; 225: 107103 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 14 |
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] |
|
| 15 |
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] |
|
| 16 |
Breast cancer intelligent analysis of histopathological data: A systematic review |
|
|
| Felipe André Zeiser, Cristiano André da Costa, Adriana Vial Roehe, Rodrigo da Rosa Righi, Nuno Miguel Cavalheiro Marques |
|
| Applied Soft Computing. 2021; 113: 107886 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 17 |
Computational methods for automated mitosis detection in histopathology images: A review |
|
|
| Tojo Mathew, Jyoti R. Kini, Jeny Rajan |
|
| Biocybernetics and Biomedical Engineering. 2021; 41(1): 64 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 18 |
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] |
|
| 19 |
A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains |
|
|
| Lyndon Chan, Mahdi S. Hosseini, Konstantinos N. Plataniotis |
|
| International Journal of Computer Vision. 2021; 129(2): 361 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 20 |
Searching Images for Consensus |
|
|
| Hamid R. Tizhoosh, Phedias Diamandis, Clinton J.V. Campbell, Amir Safarpoor, Shivam Kalra, Danial Maleki, Abtin Riasatian, Morteza Babaie |
|
| The American Journal of Pathology. 2021; 191(10): 1702 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 21 |
Deep Convolutional Neural Network for Computer-Aided Detection of Breast Cancer Using Histopathology Images |
|
|
| R Karthiga, K Narashimhan |
|
| Journal of Physics: Conference Series. 2021; 1767(1): 012042 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 22 |
SmallMitosis: Small Size Mitotic Cells Detection in Breast Histopathology Images |
|
|
| Tasleem Kausar, Mingjiang Wang, M. Adnan Ashraf, Adeeba Kausar |
|
| IEEE Access. 2021; 9: 905 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 23 |
Contextual Prior Constrained Deep Networks for Mitosis Detection With Point Annotations |
|
|
| Jiangxiao Han, Xinggang Wang, Wenyu Liu |
|
| IEEE Access. 2021; 9: 71954 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 24 |
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] |
|
| 25 |
CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance |
|
|
| Sara P. Oliveira, Pedro C. Neto, João Fraga, Diana Montezuma, Ana Monteiro, João Monteiro, Liliana Ribeiro, Sofia Gonçalves, Isabel M. Pinto, Jaime S. Cardoso |
|
| Scientific Reports. 2021; 11(1) |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 26 |
A Large-Scale Fully Annotated Low-Cost Microscopy Image Dataset for Deep Learning Framework |
|
|
| Sumona Biswas, Shovan Barma |
|
| IEEE Transactions on NanoBioscience. 2021; 20(4): 507 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 27 |
Artificial intelligence for solid tumour diagnosis in digital pathology |
|
|
| Christophe Klein, Qinghe Zeng, Floriane Arbaretaz, Estelle Devêvre, Julien Calderaro, Nicolas Lomenie, Maria Chiara Maiuri |
|
| British Journal of Pharmacology. 2021; 178(21): 4291 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 28 |
Assessment of mitotic activity in breast cancer: revisited in the digital pathology era |
|
|
| Asmaa Ibrahim, Ayat Lashen, Michael Toss, Raluca Mihai, Emad Rakha |
|
| Journal of Clinical Pathology. 2021; : jclinpath- |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 29 |
Different CNN-based Architectures for Detection of Invasive Ductal Carcinoma in Breast Using Histopathology Images |
|
|
| Isha Gupta, Sheifali Gupta, Swati Singh |
|
| International Journal of Image and Graphics. 2021; 21(05) |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 30 |
A Two-Phase Mitosis Detection Approach Based on U-Shaped Network |
|
|
| Wenjing Lu, Qiushi Zhao |
|
| BioMed Research International. 2021; 2021: 1 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 31 |
Deep Learning in Cancer Diagnosis and Prognosis Prediction: A Minireview on Challenges, Recent Trends, and Future Directions |
|
|
| Ahsan Bin Tufail, Yong-Kui Ma, Mohammed K. A. Kaabar, Francisco Martínez, A. R. Junejo, Inam Ullah, Rahim Khan, Iman Yi Liao |
|
| Computational and Mathematical Methods in Medicine. 2021; 2021: 1 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 32 |
Accuracy and efficiency of an artificial intelligence tool when counting breast mitoses |
|
|
| Liron Pantanowitz, Douglas Hartman, Yan Qi, Eun Yoon Cho, Beomseok Suh, Kyunghyun Paeng, Rajiv Dhir, Pamela Michelow, Scott Hazelhurst, Sang Yong Song, Soo Youn Cho |
|
| Diagnostic Pathology. 2020; 15(1) |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 33 |
Hyperspectral and multispectral imaging in digital and computational pathology: a systematic review [Invited] |
|
|
| Samuel Ortega, Martin Halicek, Himar Fabelo, Gustavo M. Callico, Baowei Fei |
|
| Biomedical Optics Express. 2020; 11(6): 3195 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 34 |
Class-Agnostic Weighted Normalization of Staining in Histopathology Images Using a Spatially Constrained Mixture Model |
|
|
| Sobhan Shafiei, Amir Safarpoor, Ahad Jamalizadeh, H. R. Tizhoosh |
|
| IEEE Transactions on Medical Imaging. 2020; 39(11): 3355 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 35 |
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] |
|
| 36 |
Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region |
|
|
| Marc Aubreville, Christof A. Bertram, Christian Marzahl, Corinne Gurtner, Martina Dettwiler, Anja Schmidt, Florian Bartenschlager, Sophie Merz, Marco Fragoso, Olivia Kershaw, Robert Klopfleisch, Andreas Maier |
|
| Scientific Reports. 2020; 10(1) |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 37 |
PartMitosis: A Partially Supervised Deep Learning Framework for Mitosis Detection in Breast Cancer Histopathology Images |
|
|
| Meriem Sebai, Tianjiang Wang, Saad Ali Al-Fadhli |
|
| IEEE Access. 2020; 8: 45133 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 38 |
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] |
|
| 39 |
A Comparative Evaluation of Texture Features for Semantic Segmentation of Breast Histopathological Images |
|
|
| R. Rashmi, Keerthana Prasad, Chethana Babu K. Udupa, V. Shwetha |
|
| IEEE Access. 2020; 8: 64331 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 40 |
A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks |
|
|
| Xiaomin Zhou, Chen Li, Md Mamunur Rahaman, Yudong Yao, Shiliang Ai, Changhao Sun, Qian Wang, Yong Zhang, Mo Li, Xiaoyan Li, Tao Jiang, Dan Xue, Shouliang Qi, Yueyang Teng |
|
| IEEE Access. 2020; 8: 90931 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 41 |
A large-scale optical microscopy image dataset of potato tuber for deep learning based plant cell assessment |
|
|
| Sumona Biswas, Shovan Barma |
|
| Scientific Data. 2020; 7(1) |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 42 |
A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research |
|
|
| Marc Aubreville, Christof A. Bertram, Taryn A. Donovan, Christian Marzahl, Andreas Maier, Robert Klopfleisch |
|
| Scientific Data. 2020; 7(1) |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 43 |
MaskMitosis: a deep learning framework for fully supervised, weakly supervised, and unsupervised mitosis detection in histopathology images |
|
|
| Meriem Sebai, Xinggang Wang, Tianjiang Wang |
|
| Medical & Biological Engineering & Computing. 2020; 58(7): 1603 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 44 |
Deep learning in digital pathology image analysis: a survey |
|
|
| Shujian Deng, Xin Zhang, Wen Yan, Eric I-Chao Chang, Yubo Fan, Maode Lai, Yan Xu |
|
| Frontiers of Medicine. 2020; 14(4): 470 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 45 |
Computer-Aided Histopathological Image Analysis Techniques for Automated Nuclear Atypia Scoring of Breast Cancer: a Review |
|
|
| Asha Das, Madhu S. Nair, S. David Peter |
|
| Journal of Digital Imaging. 2020; 33(5): 1091 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 46 |
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] |
|
| 47 |
Predict Ki-67 Positive Cells in H&E-Stained Images Using Deep Learning Independently From IHC-Stained Images |
|
|
| Yiqing Liu, Xi Li, Aiping Zheng, Xihan Zhu, Shuting Liu, Mengying Hu, Qianjiang Luo, Huina Liao, Mubiao Liu, Yonghong He, Yupeng Chen |
|
| Frontiers in Molecular Biosciences. 2020; 7 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 48 |
Artificial Intelligence-Based Mitosis Detection in Breast Cancer Histopathology Images Using Faster R-CNN and Deep CNNs |
|
|
| Tahir Mahmood, Muhammad Arsalan, Muhammad Owais, Min Beom Lee, Kang Ryoung Park |
|
| Journal of Clinical Medicine. 2020; 9(3): 749 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 49 |
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] |
|
| 50 |
Value of public challenges for the development of pathology deep learning algorithms |
|
|
| DouglasJoseph Hartman, JeroenA. W. M. Van Der Laak, MetinN Gurcan, Liron Pantanowitz |
|
| Journal of Pathology Informatics. 2020; 11(1): 7 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 51 |
Histo-genomics: digital pathology at the forefront of precision medicine |
|
|
| Ivraym Barsoum, Eriny Tawedrous, Hala Faragalla, George M. Yousef |
|
| Diagnosis. 2019; 6(3): 203 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 52 |
Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks |
|
|
| David Tellez, Maschenka Balkenhol, Irene Otte-Holler, Rob van de Loo, Rob Vogels, Peter Bult, Carla Wauters, Willem Vreuls, Suzanne Mol, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak, Francesco Ciompi |
|
| IEEE Transactions on Medical Imaging. 2018; 37(9): 2126 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 53 |
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] |
|
| 54 |
Machine Learning Methods for Histopathological Image Analysis |
|
|
| Daisuke Komura,Shumpei Ishikawa |
|
| Computational and Structural Biotechnology Journal. 2018; 16: 34 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 55 |
DeepMitosis: Mitosis Detection via Deep Detection, Verication and Segmentation Networks |
|
|
| Chao Li,Xinggang Wang,Wenyu Liu,Longin Jan Latecki |
|
| Medical Image Analysis. 2018; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 56 |
Digital image analysis in breast pathology –from image processing techniques to artificial intelligence |
|
|
| Stephanie Robertson,Hossein Azizpour,Kevin Smith,Johan Hartman |
|
| Translational Research. 2017; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 57 |
Gland segmentation in colon histology images: The glas challenge contest |
|
|
| Korsuk Sirinukunwattana,Josien P.W. Pluim,Hao Chen,Xiaojuan Qi,Pheng-Ann Heng,Yun Bo Guo,Li Yang Wang,Bogdan J. Matuszewski,Elia Bruni,Urko Sanchez,Anton Böhm,Olaf Ronneberger,Bassem Ben Cheikh,Daniel Racoceanu,Philipp Kainz,Michael Pfeiffer,Martin Urschler,David R.J. Snead,Nasir M. Rajpoot |
|
| Medical Image Analysis. 2017; 35: 489 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 58 |
DCAN: Deep contour-aware networks for object instance segmentation from histology images |
|
|
| Hao Chen,Xiaojuan Qi,Lequan Yu,Qi Dou,Jing Qin,Pheng-Ann Heng |
|
| Medical Image Analysis. 2017; 36: 135 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 59 |
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] |
|
| 60 |
Efficient Deep Learning Model for Mitosis Detection using Breast Histopathology Images |
|
|
| Monjoy Saha,Chandan Chakraborty,Daniel Racoceanu |
|
| Computerized Medical Imaging and Graphics. 2017; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 61 |
Deep learning in robotics: a review of recent research |
|
|
| Harry A. Pierson,Michael S. Gashler |
|
| Advanced Robotics. 2017; 31(16): 821 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 62 |
A Multi-Classifier System for Automatic Mitosis Detection in Breast Histopathology Images Using Deep Belief Networks |
|
|
| K. Sabeena Beevi,Madhu S. Nair,G. R. Bindu |
|
| IEEE Journal of Translational Engineering in Health and Medicine. 2017; 5: 1 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 63 |
SlideJ: An ImageJ plugin for automated processing of whole slide images |
|
|
| Vincenzo Della Mea,Giulia L. Baroni,David Pilutti,Carla Di Loreto,Helmut Ahammer |
|
| PLOS ONE. 2017; 12(7): e0180540 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 64 |
Introduction of Artificial Intelligence in Pathology |
|
|
| SangYong Song |
|
| Hanyang Medical Reviews. 2017; 37(2): 77 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 65 |
Using Automated Image Analysis Algorithms to Distinguish Normal, Aberrant, and Degenerate Mitotic Figures Induced by Eg5 Inhibition |
|
|
| Alison L. Bigley,Stephanie K. Klein,Barry Davies,Leigh Williams,Daniel G. Rudmann |
|
| Toxicologic Pathology. 2016; 44(5): 663 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 66 |
Adaptive Dimensionality Reduction with Semi-Supervision (AdDReSS): Classifying Multi-Attribute Biomedical Data |
|
|
| George Lee,David Edmundo Romo Bucheli,Anant Madabhushi,Daoqiang Zhang |
|
| PLOS ONE. 2016; 11(7): e0159088 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 67 |
Mitosis Counting in Breast Cancer: Object-Level Interobserver Agreement and Comparison to an Automatic Method |
|
|
| Mitko Veta,Paul J. van Diest,Mehdi Jiwa,Shaimaa Al-Janabi,Josien P. W. Pluim,Anna Sapino |
|
| PLOS ONE. 2016; 11(8): e0161286 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 68 |
Automated Segmentation of Nuclei in Breast Cancer Histopathology Images |
|
|
| Maqlin Paramanandam,Michael O’Byrne,Bidisha Ghosh,Joy John Mammen,Marie Therese Manipadam,Robinson Thamburaj,Vikram Pakrashi,Pei-Yi Chu |
|
| PLOS ONE. 2016; 11(9): e0162053 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 69 |
Image Montaging for Creating a Virtual Pathology Slide: An Innovative and Economical Tool to Obtain a Whole Slide Image |
|
|
| Spoorthi Ravi Banavar,Prashanthi Chippagiri,Rohit Pandurangappa,Saileela Annavajjula,Premalatha Bidadi Rajashekaraiah |
|
| Analytical Cellular Pathology. 2016; 2016: 1 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 70 |
Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review |
|
|
| Fuyong Xing,Lin Yang |
|
| IEEE Reviews in Biomedical Engineering. 2016; 9: 234 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 71 |
Primer for Image Informatics in Personalized Medicine |
|
|
| Young Hwan Chang,Patrick Foley,Vahid Azimi,Rohan Borkar,Jonathan Lefman |
|
| Procedia Engineering. 2016; 159: 58 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 72 |
Imagining the future of bioimage analysis |
|
|
| Erik Meijering,Anne E Carpenter,Hanchuan Peng,Fred A Hamprecht,Jean-Christophe Olivo-Marin |
|
| Nature Biotechnology. 2016; 34(12): 1250 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 73 |
A survey on automated cancer diagnosis from histopathology images |
|
|
| J. Angel Arul Jothi,V. Mary Anita Rajam |
|
| Artificial Intelligence Review. 2016; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 74 |
Quantitative analysis of nuclear shape in oral squamous cell carcinoma is useful for predicting the chemotherapeutic response |
|
|
| Maki Ogura,Yoichiro Yamamoto,Hitoshi Miyashita,Hiroyuki Kumamoto,Manabu Fukumoto |
|
| Medical Molecular Morphology. 2015; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 75 |
An unsupervised feature learning framework for basal cell carcinoma image analysis |
|
|
| John Arevalo,Angel Cruz-Roa,Viviana Arias,Eduardo Romero,Fabio A. González |
|
| Artificial Intelligence in Medicine. 2015; 64(2): 131 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 76 |
Mapping spatial heterogeneity in the tumor microenvironment: a new era for digital pathology |
|
|
| Andreas Heindl,Sidra Nawaz,Yinyin Yuan |
|
| Laboratory Investigation. 2015; 95(4): 377 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 77 |
Beyond immune density: critical role of spatial heterogeneity in estrogen receptor-negative breast cancer |
|
|
| Sidra Nawaz,Andreas Heindl,Konrad Koelble,Yinyin Yuan |
|
| Modern Pathology. 2015; 28(6): 766 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 78 |
Automated Histology Analysis: Opportunities for signal processing |
|
|
| Michael T McCann,John A. Ozolek,Carlos A. Castro,Bahram Parvin,Jelena Kovacevic |
|
| IEEE Signal Processing Magazine. 2015; 32(1): 78 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 79 |
Blind colour separation of H&E stained histological images by linearly transforming the colour space |
|
|
| R. CELIS,D. ROMO,E. ROMERO |
|
| Journal of Microscopy. 2015; 260(3): 377 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 80 |
Methods for Nuclei Detection, Segmentation, and Classification in Digital Histopathology: A Review—Current Status and Future Potential |
|
|
| Humayun Irshad,Antoine Veillard,Ludovic Roux,Daniel Racoceanu |
|
| IEEE Reviews in Biomedical Engineering. 2014; 7: 97 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 81 |
A Nonlinear Mapping Approach to Stain Normalization in Digital Histopathology Images Using Image-Specific Color Deconvolution |
|
|
| Adnan Mujahid Khan,Nasir Rajpoot,Darren Treanor,Derek Magee |
|
| IEEE Transactions on Biomedical Engineering. 2014; 61(6): 1729 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 82 |
Breast Cancer Histopathology Image Analysis: A Review |
|
|
| Mitko Veta,Josien P. W. Pluim,Paul J. van Diest,Max A. Viergever |
|
| IEEE Transactions on Biomedical Engineering. 2014; 61(5): 1400 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 83 |
Deep learning in neural networks: An overview |
|
|
| Jürgen Schmidhuber |
|
| Neural Networks. 2014; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 84 |
Assessment of algorithms for mitosis detection in breast cancer histopathology images |
|
|
| Mitko Veta,Paul J. van Diest,Stefan M. Willems,Haibo Wang,Anant Madabhushi,Angel Cruz-Roa,Fabio Gonzalez,Anders B.L. Larsen,Jacob S. Vestergaard,Anders B. Dahl,Dan C. Cire?an,Jürgen Schmidhuber,Alessandro Giusti,Luca M. Gambardella,F. Boray Tek,Thomas Walter,Ching-Wei Wang,Satoshi Kondo,Bogdan J. Matuszewski,Frederic Precioso,Violet Snell,Josef Kittler,Teofilo E. de Campos,Adnan M. Khan,Nasir M. Rajpoot,Evdokia Arkoumani,Miangela M. Lacle,Max A. Viergever,Josien P.W. Pluim |
|
| Medical Image Analysis. 2014; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 85 |
Exploring the Function of Cell Shape and Size during Mitosis |
|
|
| Clotilde Cadart,Ewa Zlotek-Zlotkiewicz,Maël Le Berre,Matthieu Piel,Helen K. Matthews |
|
| Developmental Cell. 2014; 29(2): 159 |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 86 |
Multispectral Band Selection and Spatial Characterization: Application to Mitosis Detection in Breast Cancer Histopathology |
|
|
| H. Irshad,A. Gouaillard,L. Roux,D. Racoceanu |
|
| Computerized Medical Imaging and Graphics. 2014; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
| 87 |
Cell Words: Modelling the Visual Appearance of Cells inHistopathology Images |
|
|
| Adnan M. Khan,Korsuk Sirinukunwattana,Nasir M. Rajpoot |
|
| Computerized Medical Imaging and Graphics. 2014; |
|
| [Pubmed] [Google Scholar] [DOI] |
|
