Computer-aidied diagnosis of solid breast nodules on ultrasound with digital image processing and artificial neural network

Research output: Contribution to journalConference article

40 Citations (Scopus)

Abstract

A computer-aided diagnosis algorithm identifying breast nodule malignancy using multiple ultrasonography features and aritificial neural network classifier was developed from a database of 584 hitologically-confirmed cases containing 300 benign and 284 malignant breast nodules. The features were extracted from sonographic images through digital image processing. An artificial neural network then distinguished malignant nodules based on those features. The trained artificial neural network showed the normalized area under the receiver operating characteristic curve of 0.95.

Original languageEnglish
Pages (from-to)1397-1400
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume26 II
StatePublished - 1 Dec 2004
EventConference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States
Duration: 1 Sep 20045 Sep 2004

Fingerprint

Image processing
Ultrasonics
Neural networks
Ultrasonography
Computer aided diagnosis
Classifiers

Keywords

  • Artificial neural network
  • Computer-aided diagnosis
  • Digital image processing

Cite this

@article{9e4dfead54b9410391bf9b0208fb90d1,
title = "Computer-aidied diagnosis of solid breast nodules on ultrasound with digital image processing and artificial neural network",
abstract = "A computer-aided diagnosis algorithm identifying breast nodule malignancy using multiple ultrasonography features and aritificial neural network classifier was developed from a database of 584 hitologically-confirmed cases containing 300 benign and 284 malignant breast nodules. The features were extracted from sonographic images through digital image processing. An artificial neural network then distinguished malignant nodules based on those features. The trained artificial neural network showed the normalized area under the receiver operating characteristic curve of 0.95.",
keywords = "Artificial neural network, Computer-aided diagnosis, Digital image processing",
author = "Segyeong Joo and Moon, {Woo Kyung} and Kim, {Hee Chan}",
year = "2004",
month = "12",
day = "1",
language = "English",
volume = "26 II",
pages = "1397--1400",
journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",
issn = "0589-1019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Computer-aidied diagnosis of solid breast nodules on ultrasound with digital image processing and artificial neural network

AU - Joo, Segyeong

AU - Moon, Woo Kyung

AU - Kim, Hee Chan

PY - 2004/12/1

Y1 - 2004/12/1

N2 - A computer-aided diagnosis algorithm identifying breast nodule malignancy using multiple ultrasonography features and aritificial neural network classifier was developed from a database of 584 hitologically-confirmed cases containing 300 benign and 284 malignant breast nodules. The features were extracted from sonographic images through digital image processing. An artificial neural network then distinguished malignant nodules based on those features. The trained artificial neural network showed the normalized area under the receiver operating characteristic curve of 0.95.

AB - A computer-aided diagnosis algorithm identifying breast nodule malignancy using multiple ultrasonography features and aritificial neural network classifier was developed from a database of 584 hitologically-confirmed cases containing 300 benign and 284 malignant breast nodules. The features were extracted from sonographic images through digital image processing. An artificial neural network then distinguished malignant nodules based on those features. The trained artificial neural network showed the normalized area under the receiver operating characteristic curve of 0.95.

KW - Artificial neural network

KW - Computer-aided diagnosis

KW - Digital image processing

UR - http://www.scopus.com/inward/record.url?scp=11144344411&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:11144344411

VL - 26 II

SP - 1397

EP - 1400

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

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

SN - 0589-1019

ER -