Discriminant system for severity of prostate tumor

T. Tanaka; A. Suzuki

doi:10.1007/978-3-642-03882-2_192

Discriminant system for severity of prostate tumor

T. Tanaka, A. Suzuki

Department of Applied Physics and Physico-Informatics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this study, we make a system which automatically discriminates the severity of prostate tumor. This system includes the automatic gland extraction and the support vector machine as discriminant analysis. The automatic gland extraction is difficult in recent studies because of ill-defined of glands. Also, support vector machine makes up for a fault of discriminant analysis, Mahalanobis' generalized distance which was used in recent studies. As the result of that, the rate of accuracy for discriminant is individually 96.0% as the first step , and 80.9% as the second step, so we confirm the usefulness of the algorism used in this study.

Original language	English
Title of host publication	World Congress on Medical Physics and Biomedical Engineering
Subtitle of host publication	Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics
Publisher	Springer Verlag
Pages	720-723
Number of pages	4
Edition	4
ISBN (Print)	9783642038815
DOIs	https://doi.org/10.1007/978-3-642-03882-2_192
Publication status	Published - 2009
Event	World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics - Munich, Germany Duration: 2009 Sep 7 → 2009 Sep 12

Publication series

Name	IFMBE Proceedings
Number	4
Volume	25
ISSN (Print)	1680-0737

Other

Other	World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics
Country	Germany
City	Munich
Period	09/9/7 → 09/9/12

Keywords

Automatic extraction
Prostate tumor
Support vector machine
Texture analysis

ASJC Scopus subject areas

Bioengineering
Biomedical Engineering

Access to Document

10.1007/978-3-642-03882-2_192

Fingerprint Dive into the research topics of 'Discriminant system for severity of prostate tumor'. Together they form a unique fingerprint.

Cite this

Discriminant system for severity of prostate tumor. / Tanaka, T.; Suzuki, A.

World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. 4. ed. Springer Verlag, 2009. p. 720-723 (IFMBE Proceedings; Vol. 25, No. 4).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tanaka, T & Suzuki, A 2009, Discriminant system for severity of prostate tumor. in World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. 4 edn, IFMBE Proceedings, no. 4, vol. 25, Springer Verlag, pp. 720-723, World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics, Munich, Germany, 09/9/7. https://doi.org/10.1007/978-3-642-03882-2_192

@inproceedings{bd458caf735a4c1b94f6f5bd5c03490b,

title = "Discriminant system for severity of prostate tumor",

abstract = "In this study, we make a system which automatically discriminates the severity of prostate tumor. This system includes the automatic gland extraction and the support vector machine as discriminant analysis. The automatic gland extraction is difficult in recent studies because of ill-defined of glands. Also, support vector machine makes up for a fault of discriminant analysis, Mahalanobis' generalized distance which was used in recent studies. As the result of that, the rate of accuracy for discriminant is individually 96.0% as the first step , and 80.9% as the second step, so we confirm the usefulness of the algorism used in this study.",

keywords = "Automatic extraction, Prostate tumor, Support vector machine, Texture analysis",

author = "T. Tanaka and A. Suzuki",

note = "Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics ; Conference date: 07-09-2009 Through 12-09-2009",

year = "2009",

doi = "10.1007/978-3-642-03882-2_192",

language = "English",

isbn = "9783642038815",

series = "IFMBE Proceedings",

publisher = "Springer Verlag",

number = "4",

pages = "720--723",

booktitle = "World Congress on Medical Physics and Biomedical Engineering",

edition = "4",

}

TY - GEN

T1 - Discriminant system for severity of prostate tumor

AU - Tanaka, T.

AU - Suzuki, A.

PY - 2009

Y1 - 2009

N2 - In this study, we make a system which automatically discriminates the severity of prostate tumor. This system includes the automatic gland extraction and the support vector machine as discriminant analysis. The automatic gland extraction is difficult in recent studies because of ill-defined of glands. Also, support vector machine makes up for a fault of discriminant analysis, Mahalanobis' generalized distance which was used in recent studies. As the result of that, the rate of accuracy for discriminant is individually 96.0% as the first step , and 80.9% as the second step, so we confirm the usefulness of the algorism used in this study.

AB - In this study, we make a system which automatically discriminates the severity of prostate tumor. This system includes the automatic gland extraction and the support vector machine as discriminant analysis. The automatic gland extraction is difficult in recent studies because of ill-defined of glands. Also, support vector machine makes up for a fault of discriminant analysis, Mahalanobis' generalized distance which was used in recent studies. As the result of that, the rate of accuracy for discriminant is individually 96.0% as the first step , and 80.9% as the second step, so we confirm the usefulness of the algorism used in this study.

KW - Automatic extraction

KW - Prostate tumor

KW - Support vector machine

KW - Texture analysis

UR - http://www.scopus.com/inward/record.url?scp=77950153574&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77950153574&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-03882-2_192

DO - 10.1007/978-3-642-03882-2_192

M3 - Conference contribution

AN - SCOPUS:77950153574

SN - 9783642038815

T3 - IFMBE Proceedings

SP - 720

EP - 723

BT - World Congress on Medical Physics and Biomedical Engineering

PB - Springer Verlag

T2 - World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics

Y2 - 7 September 2009 through 12 September 2009

ER -