25 citations · 112 across the 16 of their papers we have counts for
9 papers · 1 filter
Structured Model Pruning for Efficient Inference in Computational Pathology
Mohammed Adnan, Qinle Ba, Nazim Shaikh +3
Recent years have seen significant efforts to adopt Artificial Intelligence (AI) in healthcare for various use cases, from computer-aided diagnosis to ICU triage. However, the size…
Comments on 'Fast and scalable search of whole-slide images via self-supervised deep learning'
Milad Sikaroudi, Mehdi Afshari, Abubakr Shafique +2
Chen et al. [Chen2022] recently published the article 'Fast and scalable search of whole-slide images via self-supervised deep learning' in Nature Biomedical Engineering. The autho…
Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images
Shivam Kalra, Mohammed Adnan, Sobhan Hemati +3
Deep learning methods such as convolutional neural networks (CNNs) are difficult to directly utilize to analyze whole slide images (WSIs) due to the large image dimensions. We over…
Colored Kimia Path24 Dataset: Configurations and Benchmarks with Deep Embeddings
Sobhan Shafiei, Morteza Babaie, Shivam Kalra +1
The Kimia Path24 dataset has been introduced as a classification and retrieval dataset for digital pathology. Although it provides multi-class data, the color information has been…
Fine-Tuning and Training of DenseNet for Histopathology Image Representation Using TCGA Diagnostic Slides
Abtin Riasatian, Morteza Babaie, Danial Maleki +19
Feature vectors provided by pre-trained deep artificial neural networks have become a dominant source for image representation in recent literature. Their contribution to the perfo…
Representation Learning of Histopathology Images using Graph Neural Networks
Mohammed Adnan, Shivam Kalra, Hamid R. Tizhoosh
Representation learning for Whole Slide Images (WSIs) is pivotal in developing image-based systems to achieve higher precision in diagnostic pathology. We propose a two-stage frame…