A symmetric prior knowledge based deep learning model for intracerebral hemorrhage lesion segmentation

A symmetric prior knowledge based deep learning model for intracerebral hemorrhage lesion segmentation

Background: Accurate localization and classification of intracerebral hemorrhage (ICH) lesions are of great significance for the treatment and prognosis of patients with ICH. The purpose of this study is to develop a symmetric prior knowledge based deep learning model to segment ICH lesions in compu...

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Bibliographic Details
Main Authors: Mayidili Nijiati, Abudouresuli Tuersun, Yue Zhang, Qing Yuan, Ping Gong, Abudoukeyoumujiang Abulizi, Awanisa Tuoheti, Adili Abulaiti, Xiaoguang Zou
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-11-01
Series:Frontiers in Physiology
Subjects:
intracerebral hemorrhage
lesion segmentation
deep learning
symmetric knowledge
transformer
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2022.977427/full

Internet

https://www.frontiersin.org/articles/10.3389/fphys.2022.977427/full

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