Ilkay Öksüz

Orcid: 0000-0001-6478-0534

According to our database1, Ilkay Öksüz authored at least 67 papers between 2013 and 2024.

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Bibliography

2024
A Deep Learning-Based Integrated Framework for Quality-Aware Undersampled Cine Cardiac MRI Reconstruction and Analysis.
IEEE Trans. Biomed. Eng., March, 2024

GLIMS: Attention-guided lightweight multi-scale hybrid network for volumetric semantic segmentation.
Image Vis. Comput., 2024

Segmentation-aware MRI subsampling for efficient cardiac MRI reconstruction with reinforcement learning.
Image Vis. Comput., 2024

HyperCMR: Enhanced Multi-Contrast CMR Reconstruction with Eagle Loss.
CoRR, 2024

Mammographic Breast Positioning Assessment via Deep Learning.
CoRR, 2024

QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge.
CoRR, 2024

Attention-Enhanced Hybrid Feature Aggregation Network for 3D Brain Tumor Segmentation.
CoRR, 2024

Estimation of Two Dimensional Electric Field Distribution Through Deep Learning: Preliminary Study.
Proceedings of the 32nd Signal Processing and Communications Applications Conference, 2024

2023
MyoPS: A benchmark of myocardial pathology segmentation combining three-sequence cardiac magnetic resonance images.
Medical Image Anal., 2023

Explainable Image Quality Assessment for Medical Imaging.
CoRR, 2023

Semi-Supervised Segmentation of Multi-vendor and Multi-center Cardiac MRI using Histogram Matching.
CoRR, 2023

Prostate Lesion Estimation using Prostate Masks from Biparametric MRI.
CoRR, 2023

Deep Learning-Based Meniscus Tear Detection From Accelerated MRI.
IEEE Access, 2023

Block Attention and Switchable Normalization Based Deep Learning Framework for Segmentation of Retinal Vessels.
IEEE Access, 2023

Interpretable Deep Learning for Myocardial Infarction Detection from ECG Signals.
Proceedings of the 31st Signal Processing and Communications Applications Conference, 2023

Automatic Detection of Knee Osteoarthritis Severity with SOTA Deep Learning Models and Ordinal Loss.
Proceedings of the 31st Signal Processing and Communications Applications Conference, 2023

Quality Control.
Proceedings of the AI and Big Data in Cardiology: A Practical Guide, 2023

2022
Channel Attention Networks for Robust MR Fingerprint Matching.
IEEE Trans. Biomed. Eng., 2022

A Topological Loss Function for Deep-Learning Based Image Segmentation Using Persistent Homology.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Efficient MRI Reconstruction with Reinforcement Learning for Automatic Acquisition Stopping.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers, 2022

Detecting Respiratory Motion Artefacts for Cardiovascular MRIs to Ensure High-Quality Segmentation.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers, 2022

Transfer Learning Based Super Resolution of Aerial Images.
Proceedings of the 30th Signal Processing and Communications Applications Conference, 2022

Game Character Generation with Generative Adversarial Networks.
Proceedings of the 30th Signal Processing and Communications Applications Conference, 2022

Diagnosing Knee Injuries from MRI with Transformer Based Deep Learning.
Proceedings of the Predictive Intelligence in Medicine - 5th International Workshop, 2022

Shifted Windows Transformers for Medical Image Quality Assessment.
Proceedings of the Machine Learning in Medical Imaging - 13th International Workshop, 2022

Segmentation-Aware MRI Reconstruction.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2022

2021
Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-Ventricular Short-Axis Cardiac MR Data.
IEEE J. Biomed. Health Informatics, 2021

Subjective analysis of social distance monitoring using YOLO v3 architecture and crowd tracking system.
Turkish J. Electr. Eng. Comput. Sci., 2021

A survey on shape-constraint deep learning for medical image segmentation.
CoRR, 2021

Brain MRI artefact detection and correction using convolutional neural networks.
Comput. Methods Programs Biomed., 2021

Cross-domain Artefact Correction of Cardiac MRI.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge, 2021

Artifact Detection in Cardiac MRI Data by Deep Learning Methods.
Proceedings of the 29th Signal Processing and Communications Applications Conference, 2021

Semi-Supervised Segmentation of Multi-vendor and Multi-center Cardiac MRI.
Proceedings of the 29th Signal Processing and Communications Applications Conference, 2021

Explainable Image Quality Analysis of Chest X-Rays.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

Self-supervised Dynamic MRI Reconstruction.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2021

Meta-learning for Medical Image Segmentation Uncertainty Quantification.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021

2020
Deep Learning-Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation.
IEEE Trans. Medical Imaging, 2020

Channel Attention Networks for Robust MR Fingerprinting Matching.
CoRR, 2020

Transfer Learning for Electricity Price Forecasting.
CoRR, 2020

Electricity Price Prediction Using Encoder-Decoder Recurrent Neural Networks in Turkish Dayahead Market.
Proceedings of the 28th Signal Processing and Communications Applications Conference, 2020

Accurate Myocardial Pathology Segmentation with Residual U-Net.
Proceedings of the Myocardial Pathology Segmentation Combining Multi-Sequence Cardiac Magnetic Resonance Images, 2020

2019
Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning.
Medical Image Anal., 2019

dAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance.
CoRR, 2019

Detection and Correction of Cardiac MR Motion Artefacts during Reconstruction from K-space.
CoRR, 2019

High-quality segmentation of low quality cardiac MR images using k-space artefact correction.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2019

Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, 2019

Detection and Correction of Cardiac MRI Motion Artefacts During Reconstruction from k-space.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Global and Local Interpretability for Cardiac MRI Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Magnetic Resonance Fingerprinting Using Recurrent Neural Networks.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Explicit Topological Priors for Deep-Learning Based Image Segmentation Using Persistent Homology.
Proceedings of the Information Processing in Medical Imaging, 2019

Mechanically Powered Motion Imaging Phantoms: Proof of Concept.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

2018
Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge.
IEEE J. Biomed. Health Informatics, 2018

Deep Learning Using K-Space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Cardiac MR Motion Artefact Correction from K-space Using Deep Learning-Based Reconstruction.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2018

Left-Ventricle Quantification Using Residual U-Net.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, 2018

Automatic left ventricular outflow tract classification for accurate cardiac MR planning.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017
Unsupervised Myocardial Segmentation for Cardiac BOLD.
IEEE Trans. Medical Imaging, 2017

Joint Myocardial Registration and Segmentation of Cardiac BOLD MRI.
Proceedings of the Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges, 2017

2016
MRI-TRUS Image Synthesis with Application to Image-Guided Prostate Intervention.
Proceedings of the Simulation and Synthesis in Medical Imaging, 2016

2015
Dictionary Learning Based Image Descriptor for Myocardial Registration of CP-BOLD MR.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015

Supervised Learning of Functional Maps for Infarct Classification.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges, 2015

Unsupervised Myocardial Segmentation for Cardiac MRI.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

Data-Driven Feature Learning for Myocardial Segmentation of CP-BOLD MRI.
Proceedings of the Functional Imaging and Modeling of the Heart, 2015

2014
Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study.
Medical Image Anal., 2014

2013
Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed tomography angiography.
Medical Image Anal., 2013

Automated aortic supravalvular sinus detection in conventional computed tomography image.
Proceedings of the 21st Signal Processing and Communications Applications Conference, 2013

Region growing on frangi vesselness values in 3-D CTA data.
Proceedings of the 21st Signal Processing and Communications Applications Conference, 2013


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