Publications

Research in medical imaging, machine learning, and human intelligence.

1–17 of 17 publications

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2026ESGAR-2026 (Oral)

A multi-center MRI study with comprehensive radiological analysis of IPMN risk stratification with explainable AI

H. Aktas, G. Durak, A.M. Bejar, Z. Hong, R. Hendrix, H. Pan, E. Keles, F. Bol, Y. Taktak, C. Topel, Y. Tur, Z. Zhang, Y. Velichko, A. Medetalibeyoglu, S. Erturk, L. Zhao, F.H. Miller, M.B. Wallace, R.N. Keswani, U.Bagci

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2026Diagnostic and Interventional Radiology

Explainable artificial intelligence in medical imaging: how to interpret, evaluate, and use artificial intelligence explanations

Gorkem Durak, Halil Ertugrul Aktas, Tugba Akinci D'Antonoli, Ulas Bagci

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2026IEEE ACDSA 2026

Improved segmentation of polyps and visual explainability analysis

Akwasi Asare, Thanh-Huy Nguyen, Ulas Bagci

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2026Mayo Clinic Innovations in Gastroenterology and Hepatology 2026: Artificial Intelligence and Beyond

In-depth radiological and explainability analysis of deep learning

Halil Ertugrul Aktas, Andrea Mia Bejar, Ziliang Hong, Rutger Hendrix, Hongyi Pan, Elif Keles, Fergan Bol, Yavuz Bahadir Taktak, Yuri Velichko, Alpay Medetalibeyoglu, Sukru Mehmet Erturk, Lili Zhao, Frank H. Miller, Michael Wallace, Rajesh N. Keswani, Gorkem Durak, and Ulas Bagci

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2026ISMRM 2026

In-depth radiological and explainability analysis of deep learning predictions for IPMN risk stratification on MRI

Aktas, E. et al

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2026AAAI 2026 (AIMedHealth26 Workshop)

Prototype learning for out-of-distribution polyp segmentation

Nikhil Kumar Tomar, Debesh Jha, Ulas Bagci

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2026Neurocomputing

UP2D: uncertainty-aware progressive pseudo-label denoising for source-free domain adaptive medical image segmentation

Thanh-Huy Nguyen, Quang-Khai Bui-Tran, Manh D Ho, Thinh B Lam, Vi Vu, Hoang-Thien Nguyen, Phat Huynh, Ulas Bagci

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2026SABI 2026 (Chosen as Exceptional Science Scientific Session)

Uncertainty-aware explainable AI for pancreatic cysts: identifying deep learning vulnerabilities and ensuring safe clinical triage in IPMN management

Gorkem Durak, Halil Ertugrul Aktas, Andrea Mia Bejar, Ziliang Hong, Sukru Mehmet Erturk, Candice Bolan, Michael B. Wallace, Rajesh N. Keswani, Frank H. Miller, and Ulas Bagci

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2025IEEE ACDSA 2025

Uncertainty-guided coarse-to-fine tumor segmentation with anatomy-aware post-processing

Ilkin Sevgi Isler, David Mohaisen, Curtis Lisle, Damla Turgut, Ulas Bagci

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2025IEEE/CVF WACV 2025

Uncertainty-guided cross attention ensemble mean teacher for semi-supervised medical image segmentation

Meghana Karri, Amit Soni Arya, Koushik Biswas, Nicolo Gennaro, Vedat Cicek, Gorkem Durak, Yury Velichko, Ulas Bagci

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2024WACV 2024

Domain generalization with correlated style uncertainty.

Zhang, Zheyuan, et al.

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2024IEEE ISBI 2024

Explainable transformer prototypes for medical diagnoses.

Demir, Ugur, et al.

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2024RSNA 2024

MRI intensity standardization via prototype learning fro improved oncological analysis of heterogenous datasets

Meghana Karri, et al.

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2023IEEE Access - 2023

Monkeypox diagnosis with interpretable deep learning

Ahsan, Md. Manjurul, Ali, Md. Shahin, Hassan, Md. Mehedi, Abdullah, Tareque Abu, Gupta, Kishor Datta, Bagci, Ulas, Kaushal, Chetna, Soliman, Naglaa F.

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2023IEEE ICECCME 2023