System for MR brain image segmentation

Atam Dhawan; Aleksandar Zavaljevski; Alok Sarwal; Scott Holland; Mary Gaskill-Shipley; William S. Ball

System for MR brain image segmentation

Atam Dhawan, Aleksandar Zavaljevski, Alok Sarwal, Scott Holland, Mary Gaskill-Shipley, William S. Ball

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

Abstract

A system for manual segmentation of multispectral MR images into anatomical structures is described. The system consists of a SPARC workstation and a PIXAR image computer. The system simultaneously displays an enlarged working area as well as T1 weighted, and short and long echo T2 weighted images. Multiple linked cursors are also displayed for easier orientation. The operator can easily position the working area, specify the region in the working area, assign a label to the chosen region, and save the results in a file. The sophisticated man-machine interface, along with flexible choice of displayed images of the brain and their resolutions, make the system very precise and productive for manual segmentation with the interobserver variability less than 5%.

Original language	English (US)
Pages (from-to)	732-733
Number of pages	2
Journal	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume	2
State	Published - Dec 1 1996
Externally published	Yes

All Science Journal Classification (ASJC) codes

Bioengineering

Cite this

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title = "System for MR brain image segmentation",

abstract = "A system for manual segmentation of multispectral MR images into anatomical structures is described. The system consists of a SPARC workstation and a PIXAR image computer. The system simultaneously displays an enlarged working area as well as T1 weighted, and short and long echo T2 weighted images. Multiple linked cursors are also displayed for easier orientation. The operator can easily position the working area, specify the region in the working area, assign a label to the chosen region, and save the results in a file. The sophisticated man-machine interface, along with flexible choice of displayed images of the brain and their resolutions, make the system very precise and productive for manual segmentation with the interobserver variability less than 5%.",

author = "Atam Dhawan and Aleksandar Zavaljevski and Alok Sarwal and Scott Holland and Mary Gaskill-Shipley and Ball, {William S.}",

year = "1996",

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language = "English (US)",

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journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

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T1 - System for MR brain image segmentation

AU - Dhawan, Atam

AU - Zavaljevski, Aleksandar

AU - Sarwal, Alok

AU - Holland, Scott

AU - Gaskill-Shipley, Mary

AU - Ball, William S.

PY - 1996/12/1

Y1 - 1996/12/1

N2 - A system for manual segmentation of multispectral MR images into anatomical structures is described. The system consists of a SPARC workstation and a PIXAR image computer. The system simultaneously displays an enlarged working area as well as T1 weighted, and short and long echo T2 weighted images. Multiple linked cursors are also displayed for easier orientation. The operator can easily position the working area, specify the region in the working area, assign a label to the chosen region, and save the results in a file. The sophisticated man-machine interface, along with flexible choice of displayed images of the brain and their resolutions, make the system very precise and productive for manual segmentation with the interobserver variability less than 5%.

AB - A system for manual segmentation of multispectral MR images into anatomical structures is described. The system consists of a SPARC workstation and a PIXAR image computer. The system simultaneously displays an enlarged working area as well as T1 weighted, and short and long echo T2 weighted images. Multiple linked cursors are also displayed for easier orientation. The operator can easily position the working area, specify the region in the working area, assign a label to the chosen region, and save the results in a file. The sophisticated man-machine interface, along with flexible choice of displayed images of the brain and their resolutions, make the system very precise and productive for manual segmentation with the interobserver variability less than 5%.

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M3 - Article

AN - SCOPUS:0030311840

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JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

ER -

System for MR brain image segmentation

Abstract

All Science Journal Classification (ASJC) codes

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