RFDCR: Automated brain lesion segmentation using cascaded random forests with dense conditional random fields

RFDCR: Automated brain lesion segmentation using cascaded random forests with dense conditional random fields

Segmentation of brain lesions from magnetic resonance images (MRI) is an important step for disease diagnosis, surgical planning, radiotherapy and chemotherapy. However, due to noise, motion, and partial volume effects, automated segmentation of lesions from MRI is still a challenging task. In this...

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Bibliographic Details
Main Authors: Gaoxiang Chen, Qun Li, Fuqian Shi, Islem Rekik, Zhifang Pan
Format: Article
Language:English
Published: Elsevier 2020-05-01
Series:NeuroImage
Subjects:
MRI
Lesions segmentation
Brain tumor
Ischemic stroke
Random forests
Conditional random fields
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811920301075

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http://www.sciencedirect.com/science/article/pii/S1053811920301075

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