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20192023
most citedHMIC: Hierarchical Medical Image Classification, A Deep Learning Approach

65 citations · 78 across the 9 of their papers we have counts for

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5 papers · 1 filter

eess.IV2021

Cluster-to-Conquer: A Framework for End-to-End Multi-Instance Learning for Whole Slide Image Classification

Yash Sharma, Aman Shrivastava, Lubaina Ehsan +3

In recent years, the availability of digitized Whole Slide Images (WSIs) has enabled the use of deep learning-based computer vision techniques for automated disease diagnosis. Howe…

eess.IV2021★ 2 cited

Advancing Eosinophilic Esophagitis Diagnosis and Phenotype Assessment with Deep Learning Computer Vision

William Adorno, Alexis Catalano, Lubaina Ehsan +5

Eosinophilic Esophagitis (EoE) is an inflammatory esophageal disease which is increasing in prevalence. The diagnostic gold-standard involves manual review of a patient's biopsy ti…

eess.IV2020★ 65 cited

HMIC: Hierarchical Medical Image Classification, A Deep Learning Approach

Kamran Kowsari, Rasoul Sali, Lubaina Ehsan +7

Image classification is central to the big data revolution in medicine. Improved information processing methods for diagnosis and classification of digital medical images have show…

eess.IV2020

Hierarchical Deep Convolutional Neural Networks for Multi-category Diagnosis of Gastrointestinal Disorders on Histopathological Images

Rasoul Sali, Sodiq Adewole, Lubaina Ehsan +8

Deep convolutional neural networks(CNNs) have been successful for a wide range of computer vision tasks, including image classification. A specific area of the application lies in…

eess.IV2019

CeliacNet: Celiac Disease Severity Diagnosis on Duodenal Histopathological Images Using Deep Residual Networks

Rasoul Sali, Lubaina Ehsan, Kamran Kowsari +4

Celiac Disease (CD) is a chronic autoimmune disease that affects the small intestine in genetically predisposed children and adults. Gluten exposure triggers an inflammatory cascad…