Automatic bilateral symmetry (midsagittal) plane extraction from pathological 3D neuroradiological images

Yanxi Liu; Robert T. Collins; William E. Rothfus

doi:10.1117/12.310886

Automatic bilateral symmetry (midsagittal) plane extraction from pathological 3D neuroradiological images

Yanxi Liu, Robert T. Collins, William E. Rothfus

Research output: Contribution to journal › Conference article › peer-review

15 Scopus citations

Abstract

Most pathologies (tumor, bleed, stroke) of the human brain can be determined by a symmetry-based analysis of neural scans showing the brain's 3D internal structure. Detecting departures of this internal structure from its normal bilateral symmetry can guide the classification of abnormalities. This process is facilitated by first locating the ideal symmetry plane (midsagittal) with respect to which the brain is invariant under reflection. An algorithm to automatically identify this bilateral symmetry plane from a given 3D clinical image has been developed. The method has been tested on both normal and pathological brain scans, multimodal data (CT and MR), and on coarsely sliced samples with elongated voxel sizes.

Original language	English (US)
Pages (from-to)	1528-1539
Number of pages	12
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	3338
DOIs	https://doi.org/10.1117/12.310886
State	Published - 1998
Event	Medical Imaging 1998: Image Processing - San Diego, CA, United States Duration: Feb 23 1998 → Feb 23 1998

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

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10.1117/12.310886

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title = "Automatic bilateral symmetry (midsagittal) plane extraction from pathological 3D neuroradiological images",

abstract = "Most pathologies (tumor, bleed, stroke) of the human brain can be determined by a symmetry-based analysis of neural scans showing the brain's 3D internal structure. Detecting departures of this internal structure from its normal bilateral symmetry can guide the classification of abnormalities. This process is facilitated by first locating the ideal symmetry plane (midsagittal) with respect to which the brain is invariant under reflection. An algorithm to automatically identify this bilateral symmetry plane from a given 3D clinical image has been developed. The method has been tested on both normal and pathological brain scans, multimodal data (CT and MR), and on coarsely sliced samples with elongated voxel sizes.",

author = "Yanxi Liu and Collins, {Robert T.} and Rothfus, {William E.}",

year = "1998",

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journal = "Proceedings of SPIE - The International Society for Optical Engineering",

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note = "Medical Imaging 1998: Image Processing ; Conference date: 23-02-1998 Through 23-02-1998",

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T1 - Automatic bilateral symmetry (midsagittal) plane extraction from pathological 3D neuroradiological images

AU - Liu, Yanxi

AU - Collins, Robert T.

AU - Rothfus, William E.

PY - 1998

Y1 - 1998

N2 - Most pathologies (tumor, bleed, stroke) of the human brain can be determined by a symmetry-based analysis of neural scans showing the brain's 3D internal structure. Detecting departures of this internal structure from its normal bilateral symmetry can guide the classification of abnormalities. This process is facilitated by first locating the ideal symmetry plane (midsagittal) with respect to which the brain is invariant under reflection. An algorithm to automatically identify this bilateral symmetry plane from a given 3D clinical image has been developed. The method has been tested on both normal and pathological brain scans, multimodal data (CT and MR), and on coarsely sliced samples with elongated voxel sizes.

AB - Most pathologies (tumor, bleed, stroke) of the human brain can be determined by a symmetry-based analysis of neural scans showing the brain's 3D internal structure. Detecting departures of this internal structure from its normal bilateral symmetry can guide the classification of abnormalities. This process is facilitated by first locating the ideal symmetry plane (midsagittal) with respect to which the brain is invariant under reflection. An algorithm to automatically identify this bilateral symmetry plane from a given 3D clinical image has been developed. The method has been tested on both normal and pathological brain scans, multimodal data (CT and MR), and on coarsely sliced samples with elongated voxel sizes.

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JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Medical Imaging 1998: Image Processing

Y2 - 23 February 1998 through 23 February 1998

ER -

Automatic bilateral symmetry (midsagittal) plane extraction from pathological 3D neuroradiological images

Abstract

All Science Journal Classification (ASJC) codes

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