Dr. Ilkay Oksuz received 2024 ITU Young Scientist Award in Engineering  Link

Dr. Ilkay Oksuz received prestigious 2024 Parlar Research Incentive Award  Link

ITU PIMI Lab (Toygar Tanyel & Emre Kara) received  the 3rd place award in Teknofest 2024 Artificial Intelligence in Health Competition (3rd in 3000 teams) Link

ITU PIMI Lab (Ruru Xu) received  5th award in prestigious CMRxRecon 2024 Challenge in MICCAI 2024 Link  Publication

ITU PIMI Lab (Muhammed Yusuf Hansu) has won the best presentation award in Teknofest 2023 Artificial Intelligence in Health Competition (1st in 128 teams)

ITU PIMI Lab (Ahmet Karagoz) together with HEVI AI has ended up 2nd in open development phase, 4th in Open Testing Phase and 5th in Closed Testing Phase of highly competitive PICAI grand challenge on prostate cancer detection Link  Publication

ITU PIMI Lab (Yakup Abrek Er, Talha Sarı) received  the 1st place award in Teknofest 2022 Artificial Intelligence in Health Competition (1st in 128 teams) Link

ITU PIMI Lab (Sabrican Çetindağ) received  the 5st place award in QUBIQ 2021 Challenge in MICCAI 2021 (1st in 128 teams) Link

Xu, R., Oksuz, I.,  A reinforcement learning approach for optimized MRI sampling with region-specific fidelity. Neurocomputing, 2025. Online  Code

Xu, R., Oksuz, I., Segmentation-aware MRI subsampling for efficient cardiac MRI reconstruction with reinforcement learning, Image and Vision Computing 2024. Online  Code

 Alis, D., Tanyel, T., Meltem, E., Seker, M.E., Seker, D., Karaka, H.M., Karaarslan, E., Oksuz, I., 2024. Choosing the right artificial intelligence solutions for your radiology department: key factors to consider. Diagnostic and Interventional Radiology 2024. Online 

Karagoz, A., Alis, D., Seker, M.E, Zeybel G., Yergin M., Oksuz, I., Karaarslan, E., Anatomically guided self-adapting deep neural network for clinically significant prostate cancer detection on bi-parametric MRI: a multi-center study. Insights Imaging, 2023. Online 

Alis, D., Kartal, M. S., Seker, M. E., Guroz, B., Basar, Y., Arslan, A.,Sirolu S., Kurtcan S., Denizoglu N., Tuzun U., Yldrm D., Oksuz, I., Karaarslan, E.. Deep Learning for Assessing Image Quality in Bi-Parametric Prostate MRI: A Feasibility Study. European Journal of Radiology 2023. Online Bohlender S., Oksuz, I., Mukhopadhyay A., A survey on shape-constraint deep learning for medical image segmentation, IEEE Reviews in Biomedical Engineering, 2023. Online Arxiv

 Soyak R., Ersoy E.A., Navruz E., Cruz G., Prieto C., King A.P., Unay D., Oksuz, I., Channel Attention Networks for Robust MR Fingerprint Matching, IEEE Transactions on Biomedical Engineering  2021. Online

Gunduz S., Ugurlu U., Oksuz, I., Transfer Learning for Electricity Price Forecasting, Sustainable Energy, Grids and Networks 2023. Arxiv Online

Ozer C., Oksuz, I., Explainable Image Quality Analysis of Chest X-Rays, MIDL (oral acceptance rate < %15), 2021 (oral presentation). Online , Code

Oksuz, I., Brain MRI artefact detection and correction using convolutional neural networks, Computer Methods and Programs in Biomedicine(IF: 3.632), 2021, Online

Oksuz, I., Clough J.,  Ruijsink B., Puyol-Anton E.,  Bustin A., Cruz G.,, Prieto C.,  King A.P.,  Schnabel J.A., Deep Learning Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation, IEEE TMI (accepted, IF: 7.816), 2020. Online 

Clough J., Oksuz, I., Bryne N., Schnabel J.A., King A.P., Explicit topological priors for deep-learning based image segmentation using persistent homology, IPMI (acceptance rate < %25), 2019. Online

Oksuz, I., Ruijsink B., Puyol-Anton E., Clough J., Cruz G., Bustin A., Botnar R., Prieto C., Rueckert D., Schnabel J.A., King A.P., Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning, Medical Image Analysis (IF: 8.880), 2019. Online