Microcalcification detection using wavelet transform

Author

Gunawan, Dadang

Author_Institution

Electr. Eng. Dept., Univ. of Indonesia, Indonesia

Volume

2

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

694

Abstract

This paper presents a new method for detection of microcalcification using wavelet transform based on statistical methods. Digitized mammograms are decomposed using the wavelet transform without down sampling process at several levels in the transform space. In order to improve the contrast enhancement of images, the multiscale adaptive gain as an enhancement method was applied. Skewness, kurtosis and boxplot outlier were applied as detection method of the previous modification image with a specific size of region of interest. We have simulated this algorithm by using 30 variations of images as part of 18 digitized mammograms. Preliminary results show visually that applied detecting method has 96% in an effectiveness level

Keywords

cancer; image enhancement; image segmentation; mammography; medical image processing; wavelet transforms; automated detection; boxplot outlier; breast cancer; clustered microcalcification; contrast enhancement; digital mammograms; global image enhancement; kurtosis; microcalcification detection; multiscale adaptive gain; skewness; specific ROI size; statistical methods; wavelet transform; Breast cancer; Filter bank; Image reconstruction; Image sampling; Mammography; Optical microscopy; Signal resolution; Spatial resolution; Wavelet analysis; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications, Computers and signal Processing, 2001. PACRIM. 2001 IEEE Pacific Rim Conference on

Conference_Location

Victoria, BC

Print_ISBN

0-7803-7080-5

Type

conf

DOI

10.1109/PACRIM.2001.953727

Filename

953727