activity
20182026
most citedReal-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning

405 citations · 487 across the 35 of their papers we have counts for

collaborators
Showing eess.IVShow all

33 papers · 1 filter

eess.IV2025

A Reverse Mamba Attention Network for Pathological Liver Segmentation

Jun Zeng, Debesh Jha, Ertugrul Aktas +8

We present RMA-Mamba, a novel architecture that advances the capabilities of vision state space models through a specialized reverse mamba attention module (RMA). The key innovatio…

eess.IV2025

Diverse Image Generation with Diffusion Models and Cross Class Label Learning for Polyp Classification

Vanshali Sharma, Debesh Jha, M. K. Bhuyan +2

Pathologic diagnosis is a critical phase in deciding the optimal treatment procedure for dealing with colorectal cancer (CRC). Colonic polyps, precursors to CRC, can pathologically…

eess.IV2025

Liver Cirrhosis Stage Estimation from MRI with Deep Learning

Jun Zeng, Debesh Jha, Ertugrul Aktas +8

We present an end-to-end deep learning framework for automated liver cirrhosis stage estimation from multi-sequence MRI. Cirrhosis is the severe scarring (fibrosis) of the liver an…

eess.IV2024

Large Scale MRI Collection and Segmentation of Cirrhotic Liver

Debesh Jha, Onkar Kishor Susladkar, Vandan Gorade +14

Liver cirrhosis represents the end stage of chronic liver disease, characterized by extensive fibrosis and nodular regeneration that significantly increases mortality risk. While m…

eess.IV2024

Frequency-Based Federated Domain Generalization for Polyp Segmentation

Hongyi Pan, Debesh Jha, Koushik Biswas +1

Federated Learning (FL) offers a powerful strategy for training machine learning models across decentralized datasets while maintaining data privacy, yet domain shifts among client…

eess.IV20241 cited

Classification of Endoscopy and Video Capsule Images using CNN-Transformer Model

Aliza Subedi, Smriti Regmi, Nisha Regmi +3

Gastrointestinal cancer is a leading cause of cancer-related incidence and death, making it crucial to develop novel computer-aided diagnosis systems for early detection and enhanc…