HistoContours: a Framework for Visual Annotation of Histopathology Whole Slide Images
Loading...
Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
We present an end-to-end framework for histopathological analysis of whole slide images (WSIs). Our framework uses deep learning-based localization & classification of cell nuclei followed by spatial data aggregation to propagate classes of sparsely distributed nuclei across the entire slide. We use YOLO (''You Only Look Once'') for localization instead of more costly segmentation approaches and show that using HistAuGAN boosts its performance. YOLO finds bounding boxes around nuclei at good accuracy, but the classification accuracy can be improved by other methods. To this end, we extract patches around nuclei from the WSI and consider models from the SqueezeNet, ResNet, and EfficientNet families for classification. Where we do not achieve a clear separation between highest and second-highest softmax activation of the classifier, we use YOLO's output as a secondary vote. The result is a sparse annotation of the WSI, which we turn dense by using kernel density estimation. The result is a full vector of per pixel probabilities for each class of nucleus we consider. This allows us to visualize our results using both color-coding and isocontouring, reducing visual clutter. Our novel nuclei-to-tissue coupling allows histopathologists to work at both the nucleus and the tissue level, a feature appreciated by domain experts in a qualitative user study.
Description
CCS Concepts: Applied computing → Imaging; Computing methodologies → Object detection; Human-centered computing → Information visualization; Heat maps"
@inproceedings{10.2312:vcbm.20221192,
booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {Renata G. Raidou and Björn Sommer and Torsten W. Kuhlen and Michael Krone and Thomas Schultz and Hsiang-Yun Wu},
title = {{HistoContours: a Framework for Visual Annotation of Histopathology Whole Slide Images}},
author = {Al-Thelaya, Khaled and Joad, Faaiz and Gilal, Nauman Ullah and Mifsud, William and Pintore, Giovanni and Gobbetti, Enrico and Agus, Marco and Schneider, Jens},
year = {2022},
publisher = {The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-177-9},
DOI = {10.2312/vcbm.20221192}
}