Magnetic resonance image segmentation using pattern recognition, and applied to image registration and quantitation.

Abstract:

:This review highlights various magnetic resonance image (MRI) segmentation algorithms that employ pattern recognition. The procedures are grouped into two categories: low- to intermediate-level, and high-level image processing. The former consists of grey level histogram analysis, texture definition, edge identification, region growing, and contour following. The roles of significant prior knowledge, neural networks and cluster analysis are examined by producing objective identification of anatomical structures. The application of the segmented anatomical structures in image registration, to monitor the disease progression or growth of anatomy in normal volunteers and patients, is highlighted. The use of the segmented anatomy in measuring volumes of structures in normals and patients is also examined.

journal_name

NMR Biomed

journal_title

NMR in biomedicine

authors

Saeed N

doi

10.1002/(sici)1099-1492(199806/08)11:4/5<157::aid-

subject

Has Abstract

pub_date

1998-06-01 00:00:00

pages

157-67

issue

4-5

eissn

0952-3480

issn

1099-1492

pii

10.1002/(SICI)1099-1492(199806/08)11:4/5<157::AID-

journal_volume

11

pub_type

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