Results 101 to 110 of about 4,917,448 (190)

Reliability of paramagnetic rim lesion classification on quantitative susceptibility mapping (QSM) in people with multiple sclerosis: Single-site experience and systematic review. [PDF]

Mult Scler Relat Disord, 2023
Reeves JA, Mohebbi M, Zivadinov R, Bergsland N, Dwyer MG, Salman F, Schweser F, Jakimovski D.   +7 more
europepmc   +1 more source

Improving quantitative susceptibility mapping for the identification of traumatic brain injury neurodegeneration at the individual level

Zeitschrift für Medizinische Physik
Background: Emerging evidence suggests that traumatic brain injury (TBI) is a major risk factor for developing neurodegenerative disease later in life.
Juan F Domínguez D, Ashley Stewart, Alex Burmester, Hamed Akhlaghi, Kieran O'Brien, Steffen Bollmann, Karen Caeyenberghs   +6 more
doaj   +1 more source

Quantitative susceptibility mapping as an early neuroimaging biomarker for amyotrophic lateral sclerosis: A review

iRADIOLOGY
Quantitative susceptibility mapping (QSM) is an advanced post‐processing technique in magnetic resonance imaging that offers precise measurements of tissue magnetic susceptibility with impressive spatial resolution and sensitivity.
Sana Mohammadi, Sadegh Ghaderi, Farzad Fatehi   +2 more
doaj   +1 more source

Free-breathing high isotropic resolution quantitative susceptibility mapping (QSM) of liver using 3D multi-echo UTE cones acquisition and respiratory motion-resolved image reconstruction. [PDF]

Magn Reson Med, 2023
Kang M, Behr GG, Jafari R, Gambarin M, Otazo R, Kee Y.   +5 more
europepmc   +1 more source

Magnetic Susceptibility Changes in the Basal Ganglia and Brain Stem of Patients with Wilson's Disease: Evaluation with Quantitative Susceptibility Mapping

, 2018
Objectives: Wilson's disease (WD) is characterized with the accumulation of copper in the liver and brain. The objective of this study is to quantitatively measure the susceptibility changes of basal ganglia and brain stem of pediatric patients with ...
Serins, Halil Ibrahim, Selim Doganay, Mehmet Sait Dogan, Sureyya Burcu Gorkem, Duran Arslan, Gonca Koc, GÜMÜŞ, HAKAN, Hakan Gumus, Saliha Ciraci, Kazim Gumus, ARSLAN, DURAN, Gumus, Kazim, GÖRKEM, SÜREYYA BURCU, Halil Ibrahim Serin, Dogan, Mehmet Sait, Bayram, Ayse Kacar, Ayse Kacar Bayram, Abdulhakim Coskun, Doganay, Selim, Coskun, Abdulhakim, Ciraci, Saliha, Koc, Gonca   +21 more
core   +1 more source

Hemosiderin quantification in hemophilic arthropathy using quantitative magnetic resonance imaging

Scientific Reports
The goal of this study is to quantify hemosiderin deposition in the knee joint tissues of hemophilic arthropathy (HA) patients using quantitative susceptibility mapping on MRI.
Sam Sedaghat, Jame V. Luck, Annette von Drygalski, Eddie Fu, Jin Il Park, Kim Gina Gehling, Yajun Ma, Scott Ball, Eric Y. Chang, Jiang Du, Hyungseok Jang   +10 more
doaj   +1 more source

Assessing brain iron and its relationship to cognition and comorbidity in children with ADHD with quantitative susceptibility mapping (QSM)

Assessing brain iron and its relationship to cognition and comorbidity in children with ADHD with quantitative susceptibility mapping ...
Tim Silk (13098396), David Coghill (3520034), Marcel Schulze (6266402), Alexandra Philipsen (117920), Silke Lux (652101)   +4 more
core  

Decompose quantitative susceptibility mapping (QSM) to sub-voxel diamagnetic and paramagnetic components based on gradient-echo MRI data. [PDF]

Neuroimage, 2021
Chen J, Gong NJ, Chaim KT, Otaduy MCG, Liu C.   +4 more
europepmc   +1 more source

SIPAS: A comprehensive susceptibility imaging process and analysis studio

NeuroImage
Quantitative susceptibility mapping (QSM) is a rising MRI-based technology and quite a few QSM-related algorithms have been proposed to reconstruct maps of tissue susceptibility distribution from phase images.
Lichu Qiu, Zijun Zhao, Lijun Bao
doaj   +1 more source

Accelerating Phase and Quantitative susceptibility mapping with Scan-Specific Complex Convolutional Neural Networks

, 2023
International audienceMRI data is inherently complex-valued, the vast majority of deep learning frameworks do not yet support complex-valued data. Most reconstruction networks separate real and imaginary components into two separate real-valued channels,
Swetali, Nimje, de Rochefort, Ludovic, Artières, Thierry   +2 more
core   +1 more source