A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram

被引：92

作者：

Eltoukhy, Mohamed Meselhy ^{[1
]}

Faye, Ibrahima ^{[2
]}

Samir, Brahim Belhaouari ^{[2
]}

机构：

[1] Univ Teknol PETRONAS, Dept Elect & Elect Engn, Tronoh 31750, Perak, Malaysia

[2] Univ Teknol PETRONAS, Fundamental & Appl Sci Dept, Tronoh 31750, Perak, Malaysia

来源：

COMPUTERS IN BIOLOGY AND MEDICINE | 2010年 / 40卷 / 04期

关键词：

Wavelet; Curvelet; Breast cancer; Digital mammogram; Multiresolution; Feature extraction; CLASSIFICATION; MICROCALCIFICATIONS; SYSTEM;

D O I：

10.1016/j.compbiomed.2010.02.002

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

This paper presents a comparative study between wavelet and curvelet transform for breast cancer diagnosis in digital mammogram. Using multiresolution analysis, mammogram images are decomposed into different resolution levels, which are sensitive to different frequency bands. A set of the biggest coefficients from each decomposition level is extracted. Then a supervised classifier system based on Euclidian distance is constructed. The performance of the classifier is evaluated using a 2 x 5-fold cross validation followed by a statistical analysis. The experimental results suggest that curvelet transform outperforms wavelet transform and the difference is statistically significant. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：384 / 391

页数：8

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