Journal of Pathology Informatics Journal of Pathology Informatics
Contact us | Home | Login   |  Users Online: 606  Print this pageEmail this pageSmall font sizeDefault font sizeIncrease font size 

Year : 2021  |  Volume : 12  |  Issue : 1  |  Page : 29

Improving algorithm for the alignment of consecutive, whole-slide, immunohistochemical section Images

1 Department of Pathology, Fu Jen Catholic University Hospital, Fu Jen Catholic University; School of Medicine, College of Medicine, Fu Jen Catholic University; Department and Graduate Institute of Pathology, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan
2 Department of Computer Science and Information Engineering, National Taiwan University; Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University; MOST Joint Research Center for AI Technology and All Vista Healthcare, Taipei, Taiwan
3 Department of Pathology, Fu Jen Catholic University Hospital, Fu Jen Catholic University, New Taipei City, Taiwan
4 Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan

Correspondence Address:
Dr. Chiao-Min Chen
Department of Computer Science and Information Engineering, National Taiwan University, Taipei 10617
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jpi.jpi_106_20

Rights and Permissions

Background: Accurate and precise alignment of histopathology tissue sections is a key step for the interpretation of the proteome topology and cell level three-dimensional (3D) reconstruction of diseased tissues. However, the realization of an automated and robust method for aligning nonglobally stained immunohistochemical (IHC) sections is still challenging. In this study, we aim to assess the feasibility of multidimensional graph-based image registration on aligning serial-section and whole-slide IHC section images. Materials and Methods: An automated, patch graph-based registration method was established and applied to align serial, whole-slide IHC sections at ×10 magnification (average 32,947 × 27,054 pixels). The alignment began with the initial alignment of high-resolution reference and translated images (object segmentation and rigid registration) and nonlinear registration of low-resolution reference and translated images, followed by the multidimensional graph-based image registration of the segmented patches, and finally, the fusion of deformed patches for inspection. The performance of the proposed method was formulated and evaluated by the Hausdorff distance between continuous image slices. Results: Sets of average 315 patches from five serial whole slide, IHC section images were tested using 21 different IHC antibodies across five different tissue types (skin, breast, stomach, prostate, and soft tissue). The proposed method was successfully automated to align most of the images. The average Hausdorff distance was 48.93 μm with a standard deviation of 14.94 μm, showing a significant improvement from the previously published patch-based nonlinear image registration method (average Hausdorff distance of 93.89 μm with 50.85 μm standard deviation). Conclusions: Our method was effective in aligning whole-slide tissue sections at the cell-level resolution. Further advancements in the screening of the proteome topology and 3D tissue reconstruction could be expected.

Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)

 Article Access Statistics
    PDF Downloaded314    
    Comments [Add]    

Recommend this journal