Determining malignancy of brain tumors by analysis of vessel shape

Elizabeth Bullitt; Inkyung Jung; Keith Muller; Guido Gerig; Stephen Aylward; Sarang Joshi; Keith Smith; Weili Lin; Matthew Ewend

doi:10.1007/978-3-540-30136-3_79

Determining malignancy of brain tumors by analysis of vessel shape

Elizabeth Bullitt, Inkyung Jung, Keith Muller, Guido Gerig, Stephen Aylward, Sarang Joshi, Keith Smith, Weili Lin, Matthew Ewend

Biomedical Engineering

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

Abstract

Vessels supplying malignant tumors are abnormally shaped. This paper describes a blinded study that assessed tumor malignancy by analyzing vessel shape within MR images of 21 brain tumors prior to surgical resection. The program's assessment of malignancy was then compared to the final histological diagnosis. All tumors were classified correctly as benign or malignant. Of importance, malignancy-associated vessel abnormalities extend outside apparent tumor margins, thus allowing classification of even small or hemorrhagic tumors.

Original language	English (US)
Pages (from-to)	645-653
Number of pages	9
Journal	Lecture Notes in Computer Science
Volume	3217
Issue number	1 PART 2
DOIs	https://doi.org/10.1007/978-3-540-30136-3_79
State	Published - 2004
Event	Medical Image Computing and Computer-Assisted Intervention, MICCAI 2004 - 7th International Conference, Proceedings - Saint-Malo, France Duration: Sep 26 2004 → Sep 29 2004

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-30136-3_79

Cite this

@article{c276902874424093b0751bf1cff864f6,

title = "Determining malignancy of brain tumors by analysis of vessel shape",

abstract = "Vessels supplying malignant tumors are abnormally shaped. This paper describes a blinded study that assessed tumor malignancy by analyzing vessel shape within MR images of 21 brain tumors prior to surgical resection. The program's assessment of malignancy was then compared to the final histological diagnosis. All tumors were classified correctly as benign or malignant. Of importance, malignancy-associated vessel abnormalities extend outside apparent tumor margins, thus allowing classification of even small or hemorrhagic tumors.",

author = "Elizabeth Bullitt and Inkyung Jung and Keith Muller and Guido Gerig and Stephen Aylward and Sarang Joshi and Keith Smith and Weili Lin and Matthew Ewend",

year = "2004",

doi = "10.1007/978-3-540-30136-3_79",

language = "English (US)",

volume = "3217",

pages = "645--653",

journal = "Lecture Notes in Computer Science",

issn = "0302-9743",

publisher = "Springer Verlag",

number = "1 PART 2",

note = "Medical Image Computing and Computer-Assisted Intervention, MICCAI 2004 - 7th International Conference, Proceedings ; Conference date: 26-09-2004 Through 29-09-2004",

}

TY - JOUR

T1 - Determining malignancy of brain tumors by analysis of vessel shape

AU - Bullitt, Elizabeth

AU - Jung, Inkyung

AU - Muller, Keith

AU - Gerig, Guido

AU - Aylward, Stephen

AU - Joshi, Sarang

AU - Smith, Keith

AU - Lin, Weili

AU - Ewend, Matthew

PY - 2004

Y1 - 2004

N2 - Vessels supplying malignant tumors are abnormally shaped. This paper describes a blinded study that assessed tumor malignancy by analyzing vessel shape within MR images of 21 brain tumors prior to surgical resection. The program's assessment of malignancy was then compared to the final histological diagnosis. All tumors were classified correctly as benign or malignant. Of importance, malignancy-associated vessel abnormalities extend outside apparent tumor margins, thus allowing classification of even small or hemorrhagic tumors.

AB - Vessels supplying malignant tumors are abnormally shaped. This paper describes a blinded study that assessed tumor malignancy by analyzing vessel shape within MR images of 21 brain tumors prior to surgical resection. The program's assessment of malignancy was then compared to the final histological diagnosis. All tumors were classified correctly as benign or malignant. Of importance, malignancy-associated vessel abnormalities extend outside apparent tumor margins, thus allowing classification of even small or hemorrhagic tumors.

UR - http://www.scopus.com/inward/record.url?scp=11144277042&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=11144277042&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-30136-3_79

DO - 10.1007/978-3-540-30136-3_79

M3 - Conference article

AN - SCOPUS:11144277042

SN - 0302-9743

VL - 3217

SP - 645

EP - 653

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

IS - 1 PART 2

T2 - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2004 - 7th International Conference, Proceedings

Y2 - 26 September 2004 through 29 September 2004

ER -

Determining malignancy of brain tumors by analysis of vessel shape

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this