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pro vyhledávání: '"ÖZTÜRK, Şaban"'
Low-dose computed tomography (LDCT) lower potential risks linked to radiation exposure while relying on advanced denoising algorithms to maintain diagnostic quality in reconstructed images. The reigning paradigm in LDCT denoising is based on neural n
Externí odkaz:
http://arxiv.org/abs/2409.13094
Chest X-ray is an essential diagnostic tool in the identification of chest diseases given its high sensitivity to pathological abnormalities in the lungs. However, image-driven diagnosis is still challenging due to heterogeneity in size and location
Externí odkaz:
http://arxiv.org/abs/2310.06143
Magnetic resonance imaging (MRI) is an essential diagnostic tool that suffers from prolonged scan times. Reconstruction methods can alleviate this limitation by recovering clinically usable images from accelerated acquisitions. In particular, learnin
Externí odkaz:
http://arxiv.org/abs/2301.02613
Learning-based methods have recently enabled performance leaps in analysis of high-dimensional functional MRI (fMRI) time series. Deep learning models that receive as input functional connectivity (FC) features among brain regions have been commonly
Externí odkaz:
http://arxiv.org/abs/2301.00439
Broadspread use of medical imaging devices with digital storage has paved the way for curation of substantial data repositories. Fast access to image samples with similar appearance to suspected cases can help establish a consulting system for health
Externí odkaz:
http://arxiv.org/abs/2211.15371
Autor:
Güngör, Alper, Dar, Salman UH, Öztürk, Şaban, Korkmaz, Yilmaz, Elmas, Gokberk, Özbey, Muzaffer, Çukur, Tolga
Publikováno v:
A. G\"ung\"or, S. U. Dar, S. \"Ozt\"urk, Y. Korkmaz, G. Elmas, M. \"Ozbey, and T. \c{C}ukur, "Adaptive diffusion priors for accelerated MRI reconstruction," Medical Image Analysis, vol. 88, p. 102872, 2023
Deep MRI reconstruction is commonly performed with conditional models that de-alias undersampled acquisitions to recover images consistent with fully-sampled data. Since conditional models are trained with knowledge of the imaging operator, they can
Externí odkaz:
http://arxiv.org/abs/2207.05876
Publikováno v:
In Biomedical Signal Processing and Control February 2025 100 Part A
Purpose: Coronavirus 2019 (COVID-19), which emerged in Wuhan, China and affected the whole world, has cost the lives of thousands of people. Manual diagnosis is inefficient due to the rapid spread of this virus. For this reason, automatic COVID-19 de
Externí odkaz:
http://arxiv.org/abs/2011.05746
Autor:
Alenezi, Fayadh, Armghan, Ammar, Alharbi, Abdullah G., Öztürk, Şaban, Althubiti, Sara A., Mansour, Romany F.
Publikováno v:
In Expert Systems With Applications 1 December 2023 232
Publikováno v:
In Computers in Biology and Medicine December 2023 167