Retrospective T2 quantification from conventional weighted MRI of the prostate based on deep learning

Retrospective T2 quantification from conventional weighted MRI of the prostate based on deep learning

PurposeTo develop a deep learning-based method to retrospectively quantify T2 from conventional T1- and T2-weighted images.MethodsTwenty-five subjects were imaged using a multi-echo spin-echo sequence to estimate reference prostate T2 maps. Conventional T1- and T2-weighted images were acquired as th...

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Bibliographic Details
Main Authors: Haoran Sun, Lixia Wang, Timothy Daskivich, Shihan Qiu, Fei Han, Alessandro D'Agnolo, Rola Saouaf, Anthony G. Christodoulou, Hyung Kim, Debiao Li, Yibin Xie
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-10-01
Series:Frontiers in Radiology
Subjects:
prostate cancer
deep learning
multiparametric MRI
quantitative imaging
T2 mapping
peripheral zone
Online Access:https://www.frontiersin.org/articles/10.3389/fradi.2023.1223377/full

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https://www.frontiersin.org/articles/10.3389/fradi.2023.1223377/full

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