Cardiac MR Motion Artefact Correction from K-space Using Deep Learning-Based Reconstruction
MACHINE LEARNING FOR MEDICAL IMAGE RECONSTRUCTION, MLMIR 2018, Vol. 11074, No. null, 16 Eylül 2018, s. 21-29
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Deep Learning-Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation
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Image Recovery of Inaccessible Rough Surfaces Profiles Having Impedance Boundary Condition
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Detection and correction of cardiac MRI motion artefacts during reconstruction from k-space
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Segmentation-Aware MRI Reconstruction
International Workshop on Machine Learning for Medical Image Reconstruction 2022, Singapur/SİNGAPUR, 22 Eylül 2022
ACAR MERT, ÇUKUR TOLGA, ÖKSÜZ İLKAY
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Directional Total Variation Regularized Breast Tomosynthesis Image Reconstruction
2022 Medical Technologies Congress (TIPTEKNO), Antalya/TÜRKİYE, 31 Ekim 2022
DEMİREL ŞAHİN GAMZE, ERTAŞ METİN, YILDIRIM İSA
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MR image reconstruction using densely connected residual convolutional networks
Computers in Biology and Medicine, Vol. 139, Aralık 2021, ISSN: 18790534 00104825
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Projection-Based cascaded U-Net model for MR image reconstruction
Computer Methods and Programs in Biomedicine, Vol. 207, Ağustos 2021, ISSN: 18727565 01692607
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Self-supervised Dynamic MRI Reconstruction
International Workshop on Machine Learning for Medical Image Reconstruction- MICCAI 2021, Strassbourg/FRANSA, 27 Eylül 2021
ACAR MERT, ÇUKUR TOLGA, ÖKSÜZ İLKAY
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Efficient super-resolution and MR image reconstruction networks
Lisansüstü Eğitim Enstitüsü, İstanbul Teknik Üniversitesi, 2023
DURSUN ALİ EKİNCİ
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Image reconstruction with deep learning and applications in MR images
Lisansüstü Eğitim Enstitüsü, İstanbul Teknik Üniversitesi, 2022
AMIR AGHABIGLOU
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Compressed sensing based 3D image reconstruction in digital breast tomosynthesis and micro-bioimaging
Bilişim Enstitüsü, İstanbul Teknik Üniversitesi, 2018
ADEM POLAT
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Implementation of Majorization Minimization MM Algorithm for 3D Total Variation Minimization in DBT Image Reconstruction
IEEE Medical Image Analysis Conference, 29 Ekim 2016
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Sparse tomographic image reconstruction method using total variation and non local means
Imaging Systems and Techniques (IST), 2015 IEEE International Conference on, 16 Eylül 2015
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3D Digital Breast Tomosynthesis Image Reconstruction UsingAnisotropic Total Variation Minimization
2014 IEEE Engineering in Medicine and BiologyConference
S. SEYYEDİ, I. YİLDİRİM
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Evaluating the Effect of Acquisition Parameters in Digital Breast Tomosynthesis System with Iterative Reconstruction Methods on Image Quality
2013 IEEE International Conference on e-Health and Bioengineering
S. SEYYEDİ, I. YİLDİRİM, M. KAMASAK
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3 D Tomosynthesis Image Reconstruction Using Total Variation
2012 ASE/IEEE International Conference on BioMedical Computing
M. ERTAS, A. AKAN, K. CENGİZ, M. KAMASAK, S. SEYYEDİ, I. YİLDİRİM
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2D image reconstruction for tomosynthesis
2012 TIPTEKNO
S. TUZUN, I. YİLDİRİM, M. KAMASAK, A. AKAN
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Image reconstruction from sparse samples using directional total variation minimization
2016 24th Signal Processing and Communication Application Conference (SIU), 16 Mayıs 2016
DEMİRCAN TÜREYEN EZGİ,KAMAŞAK MUSTAFA ERSEL
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Sparse tomographic image reconstruction method using total variation and non local means
2015 IEEE International Conference on Imaging Systems and Techniques (IST), 16 Eylül 2015
ERTAŞ METİN,YILDIRIM İSA,KAMAŞAK MUSTAFA ERSEL,AKAN AYDIN
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