7 citations · 31 across the 47 of their papers we have counts for
19 papers · 1 filter
ProDM: Synthetic Reality-driven Property-aware Progressive Diffusion Model for Coronary Calcium Motion Correction in Non-gated Chest CT
Xinran Gong, Gorkem Durak, Halil Ertugrul Aktas +5
Coronary artery calcium (CAC) scoring from chest CT is a well-established tool to stratify and refine clinical cardiovascular disease risk estimation. CAC quantification relies on…
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…
MammoClean: Toward Reproducible and Bias-Aware AI in Mammography through Dataset Harmonization
Yalda Zafari, Hongyi Pan, Gorkem Durak +3
The development of clinically reliable artificial intelligence (AI) systems for mammography is hindered by profound heterogeneity in data quality, metadata standards, and populatio…
REN: Anatomically-Informed Mixture-of-Experts for Interstitial Lung Disease Diagnosis
Alec K. Peltekian, Halil Ertugrul Aktas, Gorkem Durak +10
Mixture-of-Experts (MoE) architectures achieve scalable learning by routing inputs to specialized subnetworks through conditional computation. However, conventional MoE designs ass…
Pancreas Part Segmentation under Federated Learning Paradigm
Ziliang Hong, Halil Ertugrul Aktas, Andrea Mia Bejar +15
We present the first federated learning (FL) approach for pancreas part(head, body and tail) segmentation in MRI, addressing a critical clinical challenge as a significant innovati…
Imaging-Based Mortality Prediction in Patients with Systemic Sclerosis
Alec K. Peltekian, Karolina Senkow, Gorkem Durak +23
Interstitial lung disease (ILD) is a leading cause of morbidity and mortality in systemic sclerosis (SSc). Chest computed tomography (CT) is the primary imaging modality for diagno…
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…
Federated Breast Cancer Detection Enhanced by Synthetic Ultrasound Image Augmentation
Hongyi Pan, Ziliang Hong, Gorkem Durak +2
Federated learning enables collaborative training of deep learning models across institutions without sharing sensitive patient data. However, its performance is often limited by s…
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…
TAGS: 3D Tumor-Adaptive Guidance for SAM
Sirui Li, Linkai Peng, Zheyuan Zhang +2
Foundation models (FMs) such as CLIP and SAM have recently shown great promise in image segmentation tasks, yet their adaptation to 3D medical imaging-particularly for pathology de…
ViCTr: Vital Consistency Transfer for Pathology Aware Image Synthesis
Onkar Susladkar, Gayatri Deshmukh, Yalcin Tur +2
Synthesizing medical images remains challenging due to limited annotated pathological data, modality domain gaps, and the complexity of representing diffuse pathologies such as liv…
Shifts in Doctors' Eye Movements Between Real and AI-Generated Medical Images
David C Wong, Bin Wang, Gorkem Durak +21
Eye-tracking analysis plays a vital role in medical imaging, providing key insights into how radiologists visually interpret and diagnose clinical cases. In this work, we first ana…
Eyes Tell the Truth: GazeVal Highlights Shortcomings of Generative AI in Medical Imaging
David Wong, Bin Wang, Gorkem Durak +23
The demand for high-quality synthetic data for model training and augmentation has never been greater in medical imaging. However, current evaluations predominantly rely on computa…
Is Long Range Sequential Modeling Necessary For Colorectal Tumor Segmentation?
Abhishek Srivastava, Koushik Biswas, Gorkem Durak +3
Segmentation of colorectal cancer (CRC) tumors in 3D medical imaging is both complex and clinically critical, providing vital support for effective radiation therapy planning and s…
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…