27 citations · 49 across the 15 of their papers we have counts for
6 papers · 1 filter
A Novel Momentum-Based Deep Learning Techniques for Medical Image Classification and Segmentation
Koushik Biswas, Ridal Pal, Shaswat Patel +10
Accurately segmenting different organs from medical images is a critical prerequisite for computer-assisted diagnosis and intervention planning. This study proposes a deep learning…
Towards Synergistic Deep Learning Models for Volumetric Cirrhotic Liver Segmentation in MRIs
Vandan Gorade, Onkar Susladkar, Gorkem Durak +7
Liver cirrhosis, a leading cause of global mortality, requires precise segmentation of ROIs for effective disease monitoring and treatment planning. Existing segmentation models of…
SAM-EG: Segment Anything Model with Egde Guidance framework for efficient Polyp Segmentation
Quoc-Huy Trinh, Hai-Dang Nguyen, Bao-Tram Nguyen Ngoc +3
Polyp segmentation, a critical concern in medical imaging, has prompted numerous proposed methods aimed at enhancing the quality of segmented masks. While current state-of-the-art…
Explainable Transformer Prototypes for Medical Diagnoses
Ugur Demir, Debesh Jha, Zheyuan Zhang +4
Deployments of artificial intelligence in medical diagnostics mandate not just accuracy and efficacy but also trust, emphasizing the need for explainability in machine decisions. T…
SynergyNet: Bridging the Gap between Discrete and Continuous Representations for Precise Medical Image Segmentation
Vandan Gorade, Sparsh Mittal, Debesh Jha +1
In recent years, continuous latent space (CLS) and discrete latent space (DLS) deep learning models have been proposed for medical image analysis for improved performance. However,…
Prototype Learning for Out-of-Distribution Polyp Segmentation
Nikhil Kumar Tomar, Debesh Jha, Ulas Bagci
Existing polyp segmentation models from colonoscopy images often fail to provide reliable segmentation results on datasets from different centers, limiting their applicability. Our…