A Mini Review on Parallel Processing of Brain Magnetic Resonance Imaging

被引：1

作者：

Kirimtat, Ayca ^{[1
]}

Krejcar, Ondrej ^{[1
]}

Dolezal, Rafael ^{[1
]}

Selamat, Ali ^{[1
,2
]}

机构：

[1] Univ Hradec Kralove, Fac Informat & Management, Ctr Basic & Appl Res, Rokitanskeho 62, Hradec Kralove 50003, Czech Republic

[2] Univ Teknol Malaysia, Malaysia Japan Int Inst Technol MJIIT, Jalan Sultan Yahya Petra, Kuala Lumpur, Malaysia

来源：

BIOINFORMATICS AND BIOMEDICAL ENGINEERING (IWBBIO 2020) | 2020年 / 12108卷

关键词：

Parallel processing; Magnetic resonance imaging; Brain; Review; RECONSTRUCTION; GRAPPA; MRI; REGISTRATION; EFFICIENCY; CORTEX;

D O I：

10.1007/978-3-030-45385-5_43

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Parallel processing is an execution of processes that make computation and calculation on many things simultaneously. In addition, parallel processing methods are applied extensively to the examination of MR imaging in treatment. As parallel computer systems become larger and faster at the present time; scientists, researchers and engineers are eventually able to find solutions to the problems in medicine, which had been taken too long to run before. Therefore, various fields including medicine and bioinformatics have already taken the advantages of parallel processing. In this review study, we deal with analyzing key concepts and eminent parallel processing methods that have been used to analyze the brain MRI images. In addition to this, we indicate great number of examples from the current literature in a comprehensive literature matrix. Based on the literature matrix that is created according to the Web of Science analysis, information graphics are presented in a comprehensive manner. As a result, parallel processing methods in brain magnetic resonance imaging offer powerful replacements to computer clusters in order to run large, disseminated solicitations.

引用

页码：482 / 493

页数：12

共 53 条

[31] Consequences of Industry 4.0 in Business and Economics [J].

Maresova, Petra ;

Soukal, Ivan ;

Svobodova, Libuse ;

Hedvicakova, Martina ;

Javanmardi, Ehsan ;

Selamat, Ali ;

Krejcar, Ondrej .

ECONOMIES, 2018, 6 (03)

[32] Fast computation of voxel-level brain connectivity maps from resting-state functional MRI using l1-norm as approximation of Pearson's temporal correlation: Proof-of-concept and example vector hardware implementation [J].

Minati, Ludovico ;

Zaca, Domenico ;

D'Incerti, Ludovico ;

Jovicich, Jorge .

MEDICAL ENGINEERING & PHYSICS, 2014, 36 (09) :1212-1217

[33] Overlapping connections within the motor cortico-basal ganglia circuit: fMRI-tractography analysis [J].

Oguri, Takuya ;

Sawamoto, Nobukatsu ;

Tabu, Hayato ;

Urayama, Shin-ichi ;

Matsuhashi, Masao ;

Matsukawa, Noriyuki ;

Ojika, Kosei ;

Fukuyama, Hidenao .

NEUROIMAGE, 2013, 78 :353-362

[34] Single-Shot Magnetic Resonance Spectroscopic Imaging with Partial Parallel Imaging [J].

Posse, Stefan ;

Otazo, Ricardo ;

Tsai, Shang-Yueh ;

Yoshimoto, Akio Ernesto ;

Lin, Fa-Hsuan .

MAGNETIC RESONANCE IN MEDICINE, 2009, 61 (03) :541-547

[35] Advances in sensitivity encoding with arbitrary k-space trajectories [J].

Pruessmann, KP ;

Weiger, M ;

Börnert, P ;

Boesiger, P .

MAGNETIC RESONANCE IN MEDICINE, 2001, 46 (04) :638-651

[36] Parallel MR Image Reconstruction Using Augmented Lagrangian Methods [J].

Ramani, Sathish ;

Fessler, Jeffrey A. .

IEEE TRANSACTIONS ON MEDICAL IMAGING, 2011, 30 (03) :694-706

[37] Parallel processing in the auditory cortex of primates [J].

Rauschecker, JP .

AUDIOLOGY AND NEURO-OTOLOGY, 1998, 3 (2-3) :86-103

[38] The LONI Pipeline Processing Environment [J].

Rex, DE ;

Ma, JQ ;

Toga, AW .

NEUROIMAGE, 2003, 19 (03) :1033-1048

[39]

Rodger James A., 2015, Informatics in Medicine Unlocked, V1, P17, DOI 10.1016/j.imu.2016.01.002

[40] GPU-accelerated elastic 3D image registration for intra-surgical applications [J].

Ruijters, Daniel ;

Romeny, Bart M. ter Haar ;

Suetens, Paul .

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2011, 103 (02) :104-112

← 1 2 3 4 5 6 →