Robust MRI abnormality detection using background noise removal with polyfit surface evolution

Robust MRI abnormality detection using background noise removal with polyfit surface evolution

Abstract Image segmentation plays a vital role in MRI abnormality detection. This paper presents a robust MRI segmentation method to outline potential abnormality blobs. Thresholding and boundary tracing strategies are employed to remove background noises, and hence, the ROIs in the whole process ar...

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Bibliographic Details
Main Authors: Changjiang Liu, Irene Cheng, Anup Basu, Jun Ye
Format: Article
Language:English
Published: SpringerOpen 2017-08-01
Series:EURASIP Journal on Image and Video Processing
Subjects:
Magnetic resonance (MR)
Segmentation
Abnormality detection
Polyfit
Bias field estimation
Level set method
Online Access:http://link.springer.com/article/10.1186/s13640-017-0209-y

Internet

http://link.springer.com/article/10.1186/s13640-017-0209-y

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