21 citations · 57 across the 34 of their papers we have counts for
35 papers
Unified CT and MRI Pancreas Segmentation for Label-Efficient Cross-Modality Subregion Transfer
Ziliang Hong, Hongyi Pan, Halil Ertugrul Aktas +7
Robust medical image segmentation across imaging modalities is challenging because of large differences in appearance and intensity distributions. Models trained on a single modali…
GazeRefine: Expert Gaze as a Test-Time Prompt for Training-Free Medical Image Segmentation
Mohammed Oussama Benyahia, Marouane Tliba, Mohamed Amine Kerkouri +10
Medical image segmentation remains difficult to scale because high-performing methods typically rely on dense expert annotations and task-specific training. We introduce GazeRefine…
Gaussian Meta-Space Augmentation for Stacking Ensembles in Multimodal IPMN Risk Stratification
Max A. Nelson, Eminenur Sen Tasci, Zhixiang Wang +12
Pancreatic cancer is among the most lethal malignancies; risk stratification of intraductal papillary mucinous neoplasms (IPMNs) offers a crucial opportunity for early intervention…
CrossPan: A Comprehensive Benchmark for Cross-Sequence Pancreas MRI Segmentation and Generalization
Linkai Peng, Cuiling Sun, Zheyuan Zhang +10
Automatic pancreas segmentation is fundamental to abdominal MRI analysis, yet deep learning models trained on one MRI sequence often fail catastrophically when applied to another-a…
Align then Refine: Text-Guided 3D Prostate Lesion Segmentation
Cuiling Sun, Linkai Peng, Adam Murphy +9
Automated 3D segmentation of prostate lesions from biparametric MRI (bp-MRI) is essential for reliable algorithmic analysis, but achieving high precision remains challenging. Volum…
GazeVaLM: A Multi-Observer Eye-Tracking Benchmark for Evaluating Clinical Realism in AI-Generated X-Rays
David Wong, Zeynep Isik, Bin Wang +22
We introduce GazeVaLM, a public eye-tracking dataset for studying clinical perception during chest radiograph authenticity assessment. The dataset comprises 960 gaze recordings fro…
Beyond Medical Diagnostics: How Medical Multimodal Large Language Models Think in Space
Quoc-Huy Trinh, Xi Ding, Yang Liu +7
Visual spatial intelligence is critical for medical image interpretation, yet remains largely unexplored in Multimodal Large Language Models (MLLMs) for 3D imaging. This gap persis…
Ensemble Models for Predicting Treatment Response in Pediatric Low-Grade Glioma Managed with Chemotherapy
Max Bengtsson, Elif Keles, Angela J. Waanders +1
In this paper, we introduce a novel pipeline for predicting chemotherapy response in pediatric brain tumors that are not amenable to complete surgical resection, using pre-treatmen…
Upstream Probabilistic Meta-Imputation for Multimodal Pediatric Pancreatitis Classification
Max A. Nelson, Elif Keles, Eminenur Sen Tasci +7
Pediatric pancreatitis is a progressive and debilitating inflammatory condition, including acute pancreatitis and chronic pancreatitis, that presents significant clinical diagnosti…
SRMA-Mamba: Spatial Reverse Mamba Attention Network for Pathological Liver Segmentation in MRI Volumes
Jun Zeng, Quoc-Huy Trinh, Deepak Ranjan Nayak +3
Liver cirrhosis plays a critical role in the prognosis of chronic liver disease. Early detection and timely intervention are essential for reducing mortality rates. However, the in…
Rethink Domain Generalization in Heterogeneous Sequence MRI Segmentation
Zheyuan Zhang, Linkai Peng, Wanying Dou +6
Clinical magnetic-resonance (MR) protocols generate many T1 and T2 sequences whose appearance differs more than the acquisition sites that produce them. Existing domain-generalizat…
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,…
Pediatric Pancreas Segmentation from MRI Scans with Deep Learning
Elif Keles, Merve Yazol, Gorkem Durak +11
Objective: Our study aimed to evaluate and validate PanSegNet, a deep learning (DL) algorithm for pediatric pancreas segmentation on MRI in children with acute pancreatitis (AP), c…
VHU-Net: Variational Hadamard U-Net for Body MRI Bias Field Correction
Xin Zhu, Ahmet Enis Cetin, Gorkem Durak +13
Bias field artifacts in magnetic resonance imaging (MRI) scans introduce spatially smooth intensity inhomogeneities that degrade image quality and hinder downstream analysis. To ad…
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…
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…
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…
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…
A New Logic For Pediatric Brain Tumor Segmentation
Max Bengtsson, Elif Keles, Gorkem Durak +5
In this paper, we present a novel approach for segmenting pediatric brain tumors using a deep learning architecture, inspired by expert radiologists' segmentation strategies. Our m…
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…
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…
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…
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…
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…