Automated segmentation of lateral ventricles from human and primate magnetic resonance images using cognition network technology.

Abstract:

:Automatic segmentation of different types of tissue from magnetic resonance images is of great importance for clinical and research applications, particularly large-scale and longitudinal studies of brain pathology. We developed a fully automated algorithm for the segmentation of lateral ventricles from cranial magnetic resonance images. This problem is of interest in the study of schizophrenia, dementia and other neuropsychiatric disorders. Our algorithm achieves comparable results to expert human raters. The theoretical approach, which is based on an emerging object-oriented technology that has been adapted and evaluated to process 3D data for the first time, may, in the future, be transferred to other important problems of magnetic resonance image analysis like gray/white matter segmentation.

journal_name

Magn Reson Imaging

authors

Schönmeyer R,Prvulovic D,Rotarska-Jagiela A,Haenschel C,Linden DE

doi

10.1016/j.mri.2006.08.013

subject

Has Abstract

pub_date

2006-12-01 00:00:00

pages

1377-87

issue

10

eissn

0730-725X

issn

1873-5894

pii

S0730-725X(06)00236-0

journal_volume

24

pub_type

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