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A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology–Radiology Fusion
Author(s) -
Khosravi Pegah,
Lysandrou Maria,
Eljalby Mahmoud,
Li Qianzi,
Kazemi Ehsan,
Zisimopoulos Pantelis,
Sigaras Alexandros,
Brendel Matthew,
Barnes Josue,
Ricketts Camir,
Meleshko Dmitry,
Yat Andy,
McClure Timothy D.,
Robinson Brian D.,
Sboner Andrea,
Elemento Olivier,
Chughtai Bilal,
Hajirasouliha Iman
Publication year - 2021
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.27599
Subject(s) - medicine , prostate cancer , biopsy , radiology , magnetic resonance imaging , receiver operating characteristic , prostate , prostate biopsy , histopathology , cancer , pathology
A definitive diagnosis of prostate cancer requires a biopsy to obtain tissue for pathologic analysis, but this is an invasive procedure and is associated with complications.