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20242026
most citedPolypDB: A Curated Multi-Center Dataset for Development of AI Algorithms in Colonoscopy

5 citations · 13 across the 17 of their papers we have counts for

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9 papers · 1 filter

eess.IV2024★ 1 cited

IPMN Risk Assessment under Federated Learning Paradigm

Hongyi Pan, Ziliang Hong, Gorkem Durak +17

Accurate classification of Intraductal Papillary Mucinous Neoplasms (IPMN) is essential for identifying high-risk cases that require timely intervention. In this study, we develop…

eess.IV2024

Adaptive Aggregation Weights for Federated Segmentation of Pancreas MRI

Hongyi Pan, Gorkem Durak, Zheyuan Zhang +16

Federated learning (FL) enables collaborative model training across institutions without sharing sensitive data, making it an attractive solution for medical imaging tasks. However…

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.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…

cs.CV2024★ 1 cited

Discrete Cosine Transform Based Decorrelated Attention for Vision Transformers

Hongyi Pan, Emadeldeen Hamdan, Xin Zhu +2

Self-attention is central to the success of Transformer architectures; however, learning the query, key, and value projections from random initialization remains challenging and co…

eess.IV2024★ 4 cited

Large-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning

Zheyuan Zhang, Elif Keles, Gorkem Durak +35

Automated volumetric segmentation of the pancreas on cross-sectional imaging is needed for diagnosis and follow-up of pancreatic diseases. While CT-based pancreatic segmentation is…