A Microcalcification Detection Using Adaptive Contrast Enhancement on Wavelet Transform and Neural Network
Summary :
Microcalcification detection is an important part of early breast cancer detection. In this paper, we propose a microcalcification detection algorithm using adaptive contrast enhancement in a mammography CAD (computer-aided diagnosis) system. The proposed microcalcification detection algorithm includes two parts. One is adaptive contrast enhancement in which the enhancement filtering parameters are determined based on noise characteristics of the mammogram. The other is a multi-stage microcalcification detection. The results show that the proposed microcalcification detection algorithm is much more robust against fluctuating noisy environments.
- Publication
- IEICE TRANSACTIONS on Information Vol.E89-D No.3 pp.1280-1287
- Publication Date
- 2006/03/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e89-d.3.1280
- Type of Manuscript
- PAPER
- Category
- Biological Engineering
Authors
Keyword
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Ho Kyung KANG, Yong Man RO, Sung Min KIM, "A Microcalcification Detection Using Adaptive Contrast Enhancement on Wavelet Transform and Neural Network" in IEICE TRANSACTIONS on Information,
vol. E89-D, no. 3, pp. 1280-1287, March 2006, doi: 10.1093/ietisy/e89-d.3.1280.
Abstract: Microcalcification detection is an important part of early breast cancer detection. In this paper, we propose a microcalcification detection algorithm using adaptive contrast enhancement in a mammography CAD (computer-aided diagnosis) system. The proposed microcalcification detection algorithm includes two parts. One is adaptive contrast enhancement in which the enhancement filtering parameters are determined based on noise characteristics of the mammogram. The other is a multi-stage microcalcification detection. The results show that the proposed microcalcification detection algorithm is much more robust against fluctuating noisy environments.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e89-d.3.1280/_p
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@ARTICLE{e89-d_3_1280,
author={Ho Kyung KANG, Yong Man RO, Sung Min KIM, },
journal={IEICE TRANSACTIONS on Information},
title={A Microcalcification Detection Using Adaptive Contrast Enhancement on Wavelet Transform and Neural Network},
year={2006},
volume={E89-D},
number={3},
pages={1280-1287},
abstract={Microcalcification detection is an important part of early breast cancer detection. In this paper, we propose a microcalcification detection algorithm using adaptive contrast enhancement in a mammography CAD (computer-aided diagnosis) system. The proposed microcalcification detection algorithm includes two parts. One is adaptive contrast enhancement in which the enhancement filtering parameters are determined based on noise characteristics of the mammogram. The other is a multi-stage microcalcification detection. The results show that the proposed microcalcification detection algorithm is much more robust against fluctuating noisy environments.},
keywords={},
doi={10.1093/ietisy/e89-d.3.1280},
ISSN={1745-1361},
month={March},}
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TY - JOUR
TI - A Microcalcification Detection Using Adaptive Contrast Enhancement on Wavelet Transform and Neural Network
T2 - IEICE TRANSACTIONS on Information
SP - 1280
EP - 1287
AU - Ho Kyung KANG
AU - Yong Man RO
AU - Sung Min KIM
PY - 2006
DO - 10.1093/ietisy/e89-d.3.1280
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E89-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2006
AB - Microcalcification detection is an important part of early breast cancer detection. In this paper, we propose a microcalcification detection algorithm using adaptive contrast enhancement in a mammography CAD (computer-aided diagnosis) system. The proposed microcalcification detection algorithm includes two parts. One is adaptive contrast enhancement in which the enhancement filtering parameters are determined based on noise characteristics of the mammogram. The other is a multi-stage microcalcification detection. The results show that the proposed microcalcification detection algorithm is much more robust against fluctuating noisy environments.
ER -
English
