15 citations · 17 across the 3 of their papers we have counts for
5 papers
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…
SlideGraph+: Whole Slide Image Level Graphs to Predict HER2Status in Breast Cancer
Wenqi Lu, Michael Toss, Emad Rakha +2
Human epidermal growth factor receptor 2 (HER2) is an important prognostic and predictive factor which is overexpressed in 15-20% of breast cancer (BCa). The determination of its s…
All You Need is Color: Image based Spatial Gene Expression Prediction using Neural Stain Learning
Muhammad Dawood, Kim Branson, Nasir M. Rajpoot +1
"Is it possible to predict expression levels of different genes at a given spatial location in the routine histology image of a tumor section by modeling its stain absorption chara…
ALBRT: Cellular Composition Prediction in Routine Histology Images
Muhammad Dawood, Kim Branson, Nasir M. Rajpoot +1
Cellular composition prediction, i.e., predicting the presence and counts of different types of cells in the tumor microenvironment from a digitized image of a Hematoxylin and Eosi…
A Generalized Meta-loss function for regression and classification using privileged information
Amina Asif, Muhammad Dawood, Fayyaz ul Amir Afsar Minhas
Learning using privileged information (LUPI) is a powerful heterogenous feature space machine learning framework that allows a machine learning model to learn from highly informati…