Spatial normalization of spine MR images for statistical correlation of lesions with clinical symptoms

Christos Davatzikos; Dengfeng Liu; Dinggang Shen; Edward H. Herskovits

doi:10.1148/radiol.2243011266

Spatial normalization of spine MR images for statistical correlation of lesions with clinical symptoms

Christos Davatzikos, Dengfeng Liu, Dinggang Shen, Edward H. Herskovits

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

An image analysis method was developed for spatial normalization of spine magnetic resonance images. A deformable shape model of the spine is first constructed, and it is subsequently used by an automated algorithm to find a shape transformation that places patient data into a stereotaxic space. Very good agreement with manual segmentations was observed. The main application of this method is in lesion-deficit analysis for determining associations between structural damage and clinical symptoms.

Original language	English (US)
Pages (from-to)	919-926
Number of pages	8
Journal	RADIOLOGY
Volume	224
Issue number	3
DOIs	https://doi.org/10.1148/radiol.2243011266
State	Published - Sep 2002
Externally published	Yes

Keywords

Computers, diagnostic aid
Model, mathematical
Spine
Stereotaxis

ASJC Scopus subject areas

Radiology Nuclear Medicine and imaging

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10.1148/radiol.2243011266

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abstract = "An image analysis method was developed for spatial normalization of spine magnetic resonance images. A deformable shape model of the spine is first constructed, and it is subsequently used by an automated algorithm to find a shape transformation that places patient data into a stereotaxic space. Very good agreement with manual segmentations was observed. The main application of this method is in lesion-deficit analysis for determining associations between structural damage and clinical symptoms.",

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AU - Davatzikos, Christos

AU - Liu, Dengfeng

AU - Shen, Dinggang

AU - Herskovits, Edward H.

PY - 2002/9

Y1 - 2002/9

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AB - An image analysis method was developed for spatial normalization of spine magnetic resonance images. A deformable shape model of the spine is first constructed, and it is subsequently used by an automated algorithm to find a shape transformation that places patient data into a stereotaxic space. Very good agreement with manual segmentations was observed. The main application of this method is in lesion-deficit analysis for determining associations between structural damage and clinical symptoms.

KW - Computers, diagnostic aid

KW - Model, mathematical

KW - Spine

KW - Stereotaxis

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Spatial normalization of spine MR images for statistical correlation of lesions with clinical symptoms

Abstract

Keywords

ASJC Scopus subject areas

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