activity
20232025
most citedLarge-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning

4 citations · 14 across the 17 of their papers we have counts for

collaborators

17 papers

eess.IV2025

Cyst-X: A Multi-Center MRI Benchmark and Federated Learning Framework for Malignancy-Risk Stratification of Pancreatic Cystic Neoplasm

Hongyi Pan, Gorkem Durak, Elif Keles +27

Pancreatic cancer is projected to be the second-deadliest cancer by 2030, making early detection critical. Intraductal papillary mucinous neoplasms (IPMNs), key cancer precursors,…

eess.IV2025

Predicting Risk of Pulmonary Fibrosis Formation in PASC Patients

Wanying Dou, Gorkem Durak, Koushik Biswas +14

While the acute phase of the COVID-19 pandemic has subsided, its long-term effects persist through Post-Acute Sequelae of COVID-19 (PASC), commonly known as Long COVID. There remai…

eess.IV2025★ 2 cited

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

Mortality Prediction of Pulmonary Embolism Patients with Deep Learning and XGBoost

Yalcin Tur, Vedat Cicek, Tufan Cinar +6

Pulmonary Embolism (PE) is a serious cardiovascular condition that remains a leading cause of mortality and critical illness, underscoring the need for enhanced diagnostic strategi…

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

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…

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.CV2024

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…

eess.IV2024

Optimizing Synthetic Data for Enhanced Pancreatic Tumor Segmentation

Linkai Peng, Zheyuan Zhang, Gorkem Durak +4

Pancreatic cancer remains one of the leading causes of cancer-related mortality worldwide. Precise segmentation of pancreatic tumors from medical images is a bottleneck for effecti…

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★ 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…

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…

cs.NE2023★ 1 cited

Adaptive Smooth Activation for Improved Disease Diagnosis and Organ Segmentation from Radiology Scans

Koushik Biswas, Debesh Jha, Nikhil Kumar Tomar +7

In this study, we propose a new activation function, called Adaptive Smooth Activation Unit (ASAU), tailored for optimized gradient propagation, thereby enhancing the proficiency o…

cs.CV2023★ 3 cited

DiffBoost: Enhancing Medical Image Segmentation via Text-Guided Diffusion Model

Zheyuan Zhang, Lanhong Yao, Bin Wang +5

Large-scale, big-variant, high-quality data are crucial for developing robust and successful deep-learning models for medical applications since they potentially enable better gene…