Deep learning algorithms for brain disease detection with magnetic induction tomography

Purpose In order to improve the reconstruction accuracy of magnetic induction tomography (MIT) and achieve fast imaging especially in the detection of cerebral hemorrhage, artificial intelligence algorithms are proposed to improve the accuracy of MIT inverse problem. Methods According to the standar...

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Bibliographic Details
Published in:	Medical physics (Lancaster) Vol. 48; no. 2; pp. 745 - 759
Main Authors:	Chen, Ruijuan, Huang, Juan, Song, Yixiang, Li, Bingnan, Wang, Jinhai, Wang, Huiquan
Format:	Journal Article
Language:	English
Published:	United States 01.02.2021
Subjects:	Algorithms Artificial Intelligence Brain - diagnostic imaging Brain Diseases cerebral hemorrhage Deep Learning DL algorithms Humans Image Processing, Computer-Assisted magnetic induction tomography Magnetic Phenomena Phantoms, Imaging reconstruction images Tomography reconstruction images cerebral hemorrhage DL algorithms magnetic induction tomography
ISSN:	0094-2405, 2473-4209, 2473-4209
Online Access:	Get full text
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