106 citations · 213 across the 42 of their papers we have counts for
6 papers · 1 filter
Quantifying Explainers of Graph Neural Networks in Computational Pathology
Guillaume Jaume, Pushpak Pati, Behzad Bozorgtabar +7
Explainability of deep learning methods is imperative to facilitate their clinical adoption in digital pathology. However, popular deep learning methods and explainability techniqu…
Anomaly Detection on X-Rays Using Self-Supervised Aggregation Learning
Behzad Bozorgtabar, Dwarikanath Mahapatra, Guillaume Vray +1
Deep anomaly detection models using a supervised mode of learning usually work under a closed set assumption and suffer from overfitting to previously seen rare anomalies at traini…
Structure Preserving Stain Normalization of Histopathology Images Using Self-Supervised Semantic Guidance
Dwarikanath Mahapatra, Behzad Bozorgtabar, Jean-Philippe Thiran +1
Although generative adversarial network (GAN) based style transfer is state of the art in histopathology color-stain normalization, they do not explicitly integrate structural info…
Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer
Christian Abbet, Inti Zlobec, Behzad Bozorgtabar +1
With the long-term rapid increase in incidences of colorectal cancer (CRC), there is an urgent clinical need to improve risk stratification. The conventional pathology report is us…
Benefiting from Bicubically Down-Sampled Images for Learning Real-World Image Super-Resolution
Mohammad Saeed Rad, Thomas Yu, Claudiu Musat +3
Super-resolution (SR) has traditionally been based on pairs of high-resolution images (HR) and their low-resolution (LR) counterparts obtained artificially with bicubic downsamplin…
Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation
Dwarikanath Mahapatra, Behzad Bozorgtabar, Jean-Philippe Thiran +1
Medical image segmentation is an important task for computer aided diagnosis. Pixelwise manual annotations of large datasets require high expertise and is time consuming. Conventio…