2 citations · 5 across the 5 of their papers we have counts for
5 papers
Synthesis of Annotated Colorectal Cancer Tissue Images from Gland Layout
Srijay Deshpande, Fayyaz Minhas, Nasir Rajpoot
Generating realistic tissue images with annotations is a challenging task that is important in many computational histopathology applications. Synthetically generated images and an…
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Simon Graham, Quoc Dang Vu, Mostafa Jahanifar +86
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovatio…
SynCLay: Interactive Synthesis of Histology Images from Bespoke Cellular Layouts
Srijay Deshpande, Muhammad Dawood, Fayyaz Minhas +1
Automated synthesis of histology images has several potential applications in computational pathology. However, no existing method can generate realistic tissue images with a bespo…
Cellular Segmentation and Composition in Routine Histology Images using Deep Learning
Muhammad Dawood, Raja Muhammad Saad Bashir, Srijay Deshpande +2
Identification and quantification of nuclei in colorectal cancer haematoxylin \& eosin (H\&E) stained histology images is crucial to prognosis and patient management. In computatio…
SAFRON: Stitching Across the Frontier for Generating Colorectal Cancer Histology Images
Srijay Deshpande, Fayyaz Minhas, Simon Graham +1
Synthetic images can be used for the development and evaluation of deep learning algorithms in the context of limited availability of data. In the field of computational pathology,…