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Ulsan Univ. Repository Journal Papers Medicine Medicine

Deep-learned time-signal intensity pattern analysis using an autoencoder captures magnetic resonance perfusion heterogeneity for brain tumor differentiation

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Author(s): 박지은; 김호성; 이준규; 정이내; 신일아; 안성수; 심우현; 박지은; 김호성; 이준규; 정이내; 신일아; 안성수; 심우현

Issued Date: 2020

Type: Article

Keyword: DEEP learning; BRAIN tumors; IMAGE processing; MAGNETIC resonance imaging; TUMOR diagnosis; ARTIFICIAL neural networks; LYMPHOMAS

DOI: 10.1038/s41598-020-78485-x

URI: https://oak.ulsan.ac.kr/handle/2021.oak/11912

Publisher: SCIENTIFIC REPORTS

Language: 영어

ISSN: 2045-2322

Citation Volume: 10

Citation Number: 1

Citation Start Page: 21485

Citation End Page: 21485

Appears in Collections:: Medicine > Medicine

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