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

65 citations · 65 across the 2 of their papers we have counts for

collaborators

5 papers

eess.IV202065 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

Self-Attentive Adversarial Stain Normalization

Aman Shrivastava, Will Adorno, Yash Sharma +7

Hematoxylin and Eosin (H&E) stained Whole Slide Images (WSIs) are utilized for biopsy visualization-based diagnostic and prognostic assessment of diseases. Variation in the H&E sta…

q-bio.QM2019

Deep Learning for Visual Recognition of Environmental Enteropathy and Celiac Disease

Aman Shrivastava, Karan Kant, Saurav Sengupta +8

Physicians use biopsies to distinguish between different but histologically similar enteropathies. The range of syndromes and pathologies that could cause different gastrointestina…

eess.IV2019

Diagnosis of Celiac Disease and Environmental Enteropathy on Biopsy Images Using Color Balancing on Convolutional Neural Networks

Kamran Kowsari, Rasoul Sali, Marium N. Khan +7

Celiac Disease (CD) and Environmental Enteropathy (EE) are common causes of malnutrition and adversely impact normal childhood development. CD is an autoimmune disorder that is pre…