1 citations · 2 across the 17 of their papers we have counts for
22 papers
Anatomy-Aware Prediction of Bronchoscopic Accessibility from 3D CT
Linkai Peng, Cuiling Sun, Bin Wang +11
Pre-operative planning for bronchoscopy is critical for the diagnosis of lung lesions. Current accessibility assessment relies on subjective manual inspection of CT scans, which is…
Serverless gossip training of LSTM failure detectors: A matched-protocol comparison with federated, local and centralized learning on NASA C-MAPSS
Yusuf Öztürk, Enes Göktekin, Bengisu Atlı +3
Industrial predictive maintenance increasingly depends on learning from equipment spread across sites whose sensor data cannot easily be pooled. Federated averaging (FedAvg) solves…
Decentralized Gossip Learning and Federated Averaging for Histopathology Image Classification
Yusuf Ozturk, Enes Goltekin, Bengisu Atli +3
Breast histopathology analysis increasingly relies on distributed learning because direct data pooling across institutions is often restricted by privacy, governance, and communica…
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…
Hierarchical MoE for Multi-Modal ILD Diagnosis
Alec K. Peltekian, Gorkem Durak, Halil Ertugrul Aktas +9
Mixture-of-experts (MoE) models combine specialized predictors under learned routing, offering a principled mechanism for leveraging heterogeneity in medical data. We present a hie…
A decodability criterion predicts when hidden-state selection beats majority voting in large language models
Zhixiang wang, Ziliang Hong, Ulas Bagci
Combining the answers a large language model (LLM) samples for a question into one decision is a test-time information fusion problem, usually solved by majority voting. Voting is…
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…
BreastMammo and DenseMammo: Benchmarks for Mammography Domain Generalization
Hongyi Pan, Gorkem Durak, Halil Ertugrul Aktas +18
Breast density classification is a critical component of breast cancer risk assessment, yet AI models often struggle to generalize across clinical sites due to vendor-specific acqu…
CT-DegradBench: A Physics-Informed Benchmark for CT Degradation Detection and Severity Estimation
Yousra Nabila Taifour, Marouane Tliba, Zuheng Ming +9
Computed tomography (CT) images are frequently degraded by acquisition artifacts, including noise, blur, streaking, aliasing, and metal artifacts. Yet CT enhancement is still large…
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…
Hybrid Multi-Dimensional MRI Prostate Cancer Detection via Hadamard Network-Based Bias Correction and Residual Networks
Emadeldeen Hamdan, Gorkem Durak, Muhammed Enes Tasci +7
Magnetic Resonance Imaging (MRI) is vital for prostate cancer (PCa) diagnosis. While advanced techniques such as Hybrid Multi-dimensional MRI (HM-MRI) have enhanced diagnostic capa…
CORA: Generalizable coronary artery disease assessment and risk stratification from coronary CT angiography using pathology-centric representation learning
Jinkui Hao, Gorkem Durak, Halil Ertugrul Aktas +4
Coronary artery disease, a leading cause of cardiovascular mortality worldwide, can be assessed non-invasively by coronary computed tomography angiography (CCTA). Although deep lea…
LUMINA: A Multi-Vendor Mammography Benchmark with Energy Harmonization Protocol
Hongyi Pan, Gorkem Durak, Halil Ertugrul Aktas +9
Publicly available full-field digital mammography (FFDM) datasets remain limited in size, clinical annotations, and vendor diversity, hindering the development of robust models. We…
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…
CTest-Metric: A Unified Framework to Assess Clinical Validity of Metrics for CT Report Generation
Vanshali Sharma, Andrea Mia Bejar, Gorkem Durak +1
In the generative AI era, where even critical medical tasks are increasingly automated, radiology report generation (RRG) continues to rely on suboptimal metrics for quality assess…
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…
AI Powered Road Network Prediction with Multi-Modal Data
Necip Enes Gengec, Ergin Tari, Ulas Bagci
This study presents an innovative approach for automatic road detection with deep learning, by employing fusion strategies for utilizing both lower-resolution satellite imagery and…