Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Mehmet Akçakaya"'
Autor:
Logan T. Dowdle, Luca Vizioli, Steen Moeller, Mehmet Akçakaya, Cheryl Olman, Geoffrey Ghose, Essa Yacoub, Kâmil Uğurbil
Publikováno v:
NeuroImage, Vol 270, Iss , Pp 119949- (2023)
As the neuroimaging field moves towards detecting smaller effects at higher spatial resolutions, and faster sampling rates, there is increased attention given to the deleterious contribution of unstructured, thermal noise. Here, we critically evaluat
Externí odkaz:
https://doaj.org/article/365a29a760114a59a87e53bae66ee5ae
Autor:
Luca Vizioli, Steen Moeller, Logan Dowdle, Mehmet Akçakaya, Federico De Martino, Essa Yacoub, Kamil Uğurbil
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-15 (2021)
The signal-to-noise ratio is a key consideration when selecting a magnetic resonance imaging protocol. Thermal noise is major issue, especially in high resolution functional images. Here the authors introduce a method to suppress thermal noise in fun
Externí odkaz:
https://doaj.org/article/49878964c36e40e8b136437922f9a56a
Autor:
Sebastian Weingärtner, Ömer B. Demirel, Francisco Gama, Iain Pierce, Thomas A. Treibel, Jeanette Schulz-Menger, Mehmet Akçakaya
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 9 (2022)
Late gadolinium enhancement (LGE) with cardiac magnetic resonance (CMR) imaging is the clinical reference for assessment of myocardial scar and focal fibrosis. However, current LGE techniques are confined to imaging of a single cardiac phase, which h
Externí odkaz:
https://doaj.org/article/7296765dcd6844afb95af6ab831dfc1d
Publikováno v:
NeuroImage, Vol 256, Iss , Pp 119248- (2022)
Parallel imaging is the most clinically used acceleration technique for magnetic resonance imaging (MRI) in part due to its easy inclusion into routine acquisitions. In k-space based parallel imaging reconstruction, sub-sampled k-space data are inter
Externí odkaz:
https://doaj.org/article/08ee53b0a1e148fc9a28273c5479d18d
Autor:
Felipe Kazmirczak, Prabhjot S. Nijjar, Lei Zhang, Andrew Hughes, Ko-Hsuan Amy Chen, Osama Okasha, Cindy M. Martin, Mehmet Akçakaya, Afshin Farzaneh-Far, Chetan Shenoy
Publikováno v:
Journal of Cardiovascular Magnetic Resonance, Vol 21, Iss 1, Pp 1-8 (2019)
Abstract Background There is a critical need for non-invasive methods to detect coronary allograft vasculopathy and to risk stratify heart transplant recipients. Vasodilator stress testing using cardiovascular magnetic resonance imaging (CMR) is a pr
Externí odkaz:
https://doaj.org/article/c039d8104c5c4a679f67096749028460
Autor:
Steen Moeller, Pramod Kumar Pisharady, Sudhir Ramanna, Christophe Lenglet, Xiaoping Wu, Logan Dowdle, Essa Yacoub, Kamil Uğurbil, Mehmet Akçakaya
Publikováno v:
NeuroImage, Vol 226, Iss , Pp 117539- (2021)
Diffusion-weighted magnetic resonance imaging (dMRI) has found great utility for a wide range of neuroscientific and clinical applications. However, high-resolution dMRI, which is required for improved delineation of fine brain structures and connect
Externí odkaz:
https://doaj.org/article/664575c6b0dc48a994be1b79ef03a967
Autor:
Ruoyun Ma, Mehmet Akçakaya, Steen Moeller, Edward Auerbach, Kâmil Uğurbil, Pierre-François Van de Moortele
Publikováno v:
NeuroImage, Vol 216, Iss , Pp 116861- (2020)
Over the recent years, significant advances in Spin-Echo (SE) Echo-Planar (EP) Diffusion MRI (dMRI) have enabled improved fiber tracking conspicuity in the human brain. At the same time, pushing the spatial resolution and using higher b-values inhere
Externí odkaz:
https://doaj.org/article/f45c17ad8109447bb3d6c7b7865a6a25
Autor:
Seyed Amir Hossein Hosseini, Chi Zhang, Sebastian Weingärtner, Steen Moeller, Matthias Stuber, Kamil Ugurbil, Mehmet Akçakaya
Publikováno v:
PLoS ONE, Vol 15, Iss 2, p e0229418 (2020)
PURPOSE:To accelerate coronary MRI acquisitions with arbitrary undersampling patterns by using a novel reconstruction algorithm that applies coil self-consistency using subject-specific neural networks. METHODS:Self-consistent robust artificial-neura
Externí odkaz:
https://doaj.org/article/6dde408971a142acadee46eeb4a3a4fa
Autor:
Chi Zhang, Seyed Amir Hossein Hosseini, Sebastian Weingärtner, Kâmil Uǧurbil, Steen Moeller, Mehmet Akçakaya
Publikováno v:
PLoS ONE, Vol 14, Iss 10, p e0223315 (2019)
BackgroundRobust Artificial-neural-networks for k-space Interpolation (RAKI) is a recently proposed deep-learning-based reconstruction algorithm for parallel imaging. Its main premise is to perform k-space interpolation using convolutional neural net
Externí odkaz:
https://doaj.org/article/77af0886442e4e21861b37a42e7fe6c3
Publikováno v:
PLoS ONE, Vol 10, Iss 2, p e0112020 (2015)
Coronary magnetic resonance imaging (MRI) requires a correctly timed trigger delay derived from a scout cine scan to synchronize k-space acquisition with the quiescent period of the cardiac cycle. However, heart rate changes between breath-held cine
Externí odkaz:
https://doaj.org/article/359969a551df4ee0adad4ace975c291e