FBIseg tool for the visible human project

Gobert Lee; Mariusz Bajger; Martin Caon

doi:10.1007/s11548-014-1018-8

Abstract

The purpose of this paper is to introduce the Full-Body Image segmentation tool, FBIseg, for Visible Human Project and similar projects around the world. Currently, full body image segmentation is typically performed manually with different level of computer assistance. It is laborious and prohibitive. The FBIseg developed by our group combines the state-or-the-art machine segmentation capability with human expert knowledge to attain efficiency and accuracy in full-body segmentation. The FBIseg tool was written in the Java programming language for its portability. Key features in the FBIseg tool include the use of multiple segmentation techniques on a dataset (e.g. CT scan of a single subject) and the switching of segmentation algorithms from one slice image to another for optimizing segmentation efficiency and accuracy.

Original language	English
Pages (from-to)	S40
Number of pages	1
Journal	International Journal of CARS
Volume	9
Issue number	Supp 1
DOIs	https://doi.org/10.1007/s11548-014-1018-8
Publication status	Published - May 2014
Event	28th International Congress and Exhibition on Computer Assisted Radiology and Surgery - Fukuoka, Japan Duration: 25 Jun 2014 → 28 Jun 2014 Conference number: 28th

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title = "FBIseg tool for the visible human project",

abstract = "The purpose of this paper is to introduce the Full-Body Image segmentation tool, FBIseg, for Visible Human Project and similar projects around the world. Currently, full body image segmentation is typically performed manually with different level of computer assistance. It is laborious and prohibitive. The FBIseg developed by our group combines the state-or-the-art machine segmentation capability with human expert knowledge to attain efficiency and accuracy in full-body segmentation. The FBIseg tool was written in the Java programming language for its portability. Key features in the FBIseg tool include the use of multiple segmentation techniques on a dataset (e.g. CT scan of a single subject) and the switching of segmentation algorithms from one slice image to another for optimizing segmentation efficiency and accuracy.",

author = "Gobert Lee and Mariusz Bajger and Martin Caon",

year = "2014",

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doi = "10.1007/s11548-014-1018-8",

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T1 - FBIseg tool for the visible human project

AU - Lee, Gobert

AU - Bajger, Mariusz

AU - Caon, Martin

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PY - 2014/5

Y1 - 2014/5

N2 - The purpose of this paper is to introduce the Full-Body Image segmentation tool, FBIseg, for Visible Human Project and similar projects around the world. Currently, full body image segmentation is typically performed manually with different level of computer assistance. It is laborious and prohibitive. The FBIseg developed by our group combines the state-or-the-art machine segmentation capability with human expert knowledge to attain efficiency and accuracy in full-body segmentation. The FBIseg tool was written in the Java programming language for its portability. Key features in the FBIseg tool include the use of multiple segmentation techniques on a dataset (e.g. CT scan of a single subject) and the switching of segmentation algorithms from one slice image to another for optimizing segmentation efficiency and accuracy.

AB - The purpose of this paper is to introduce the Full-Body Image segmentation tool, FBIseg, for Visible Human Project and similar projects around the world. Currently, full body image segmentation is typically performed manually with different level of computer assistance. It is laborious and prohibitive. The FBIseg developed by our group combines the state-or-the-art machine segmentation capability with human expert knowledge to attain efficiency and accuracy in full-body segmentation. The FBIseg tool was written in the Java programming language for its portability. Key features in the FBIseg tool include the use of multiple segmentation techniques on a dataset (e.g. CT scan of a single subject) and the switching of segmentation algorithms from one slice image to another for optimizing segmentation efficiency and accuracy.

U2 - 10.1007/s11548-014-1018-8

DO - 10.1007/s11548-014-1018-8

M3 - Meeting Abstract

SN - 1861-6429

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SP - S40

JO - International Journal of CARS

JF - International Journal of CARS

IS - Supp 1

T2 - 28th International Congress and Exhibition on Computer Assisted Radiology and Surgery

Y2 - 25 June 2014 through 28 June 2014

ER -

FBIseg tool for the visible human project

Abstract

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