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20232025
most citedPolypDB: A Curated Multi-Center Dataset for Development of AI Algorithms in Colonoscopy

5 citations · 13 across the 15 of their papers we have counts for

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Showing 2024Show all

10 papers · 1 filter

cs.CV2024

Uncertainty-Guided Cross Attention Ensemble Mean Teacher for Semi-supervised Medical Image Segmentation

Meghana Karri, Amit Soni Arya, Koushik Biswas +5

This work proposes a novel framework, Uncertainty-Guided Cross Attention Ensemble Mean Teacher (UG-CEMT), for achieving state-of-the-art performance in semi-supervised medical imag…

eess.IV2024★ 1 cited

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…

cs.CV2024★ 5 cited

PolypDB: A Curated Multi-Center Dataset for Development of AI Algorithms in Colonoscopy

Debesh Jha, Nikhil Kumar Tomar, Vanshali Sharma +19

Colonoscopy is the primary method for examination, detection, and removal of polyps. However, challenges such as variations among the endoscopists' skills, bowel quality preparatio…

cs.CV2024★ 2 cited

Transformer-Enhanced Iterative Feedback Mechanism for Polyp Segmentation

Nikhil Kumar Tomar, Debesh Jha, Koushik Biswas +4

Colorectal cancer (CRC) is the third most common cause of cancer diagnosed in the United States and the second leading cause of cancer-related death among both genders. Notably, CR…

cs.CV2024

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…

cs.CY2024★ 1 cited

Ethical Framework for Responsible Foundational Models in Medical Imaging

Debesh Jha, Gorkem Durak, Abhijit Das +33

The emergence of foundational models represents a paradigm shift in medical imaging, offering extraordinary capabilities in disease detection, diagnosis, and treatment planning. Th…

eess.IV2024

MDNet: Multi-Decoder Network for Abdominal CT Organs Segmentation

Debesh Jha, Nikhil Kumar Tomar, Koushik Biswas +11

Accurate segmentation of organs from abdominal CT scans is essential for clinical applications such as diagnosis, treatment planning, and patient monitoring. To handle challenges o…

eess.IV2024

PAM-UNet: Shifting Attention on Region of Interest in Medical Images

Abhijit Das, Debesh Jha, Vandan Gorade +7

Computer-aided segmentation methods can assist medical personnel in improving diagnostic outcomes. While recent advancements like UNet and its variants have shown promise, they fac…

eess.IV2024

Detection of Peri-Pancreatic Edema using Deep Learning and Radiomics Techniques

Ziliang Hong, Debesh Jha, Koushik Biswas +9

Identifying peri-pancreatic edema is a pivotal indicator for identifying disease progression and prognosis, emphasizing the critical need for accurate detection and assessment in p…

eess.IV2024★ 1 cited

CT Liver Segmentation via PVT-based Encoding and Refined Decoding

Debesh Jha, Nikhil Kumar Tomar, Koushik Biswas +7

Accurate liver segmentation from CT scans is essential for effective diagnosis and treatment planning. Computer-aided diagnosis systems promise to improve the precision of liver di…