title: Comparing the performance of image enhancement methods to detect microcalcification clusters in digital mammography.
abstract: BACKGROUND
  Mammography is the primary imaging technique for detection and diagnosis of breast cancer; however, the contrast of a mammogram image is often poor, especially for dense and glandular tissues. In these cases the radiologist may miss some diagnostically important microcalcifications. In order to improve diagnosis of cancer correctly, image enhancement technology is often used to enhance the image and help radiologists.
  
  
  METHODS
  This paper presents a comparative study in digital mammography image enhancement based on four different algorithms: wavelet-based enhancement (Asymmetric Daubechies of order 8), Contrast-Limited Adaptive Histogram Equalization (CLAHE), morphological operators and unsharp masking. These algorithms have been tested on 114 clinical digital mammography images. The comparison for all the proposed image enhancement techniques was carried out to find out the best technique in enhancement of the mammogram images to detect microcalcifications.
  
  
  RESULTS
  For evaluation of performance of image enhancement algorithms, the Contrast Improvement Index (CII) and profile intensity surface area distribution curve quality assessment have been used after any enhancement. The results of this study have shown that the average of CII is about 2.61 for wavelet and for CLAHE, unsharp masking and morphology operation are about 2.047, 1.63 and 1.315 respectively.
  
  
  CONCLUSIONS
  Experimental results strongly suggest that the wavelet transformation can be more effective and improve significantly overall detection of the Computer-Aided Diagnosis (CAD) system especially for dense breast. Compare to other studies, our method achieved a higher CII.
authors: Dept. of Biomedical Radiation Engineering, Amirkabir University of Technology, Tehran, Iran.
authors: Hajar
authors: H
authors: Moradmand
authors: Dept. of Biomedical Radiation Engineering, Amirkabir University of Technology, Tehran, Iran.
authors: Saeed
authors: S
authors: Setayeshi
authors: Dept. of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran.
authors: Ali Reza
authors: AR
authors: Karimian
authors: Isfahan University of Medical Sciences, Isfahan, Iran.
authors: Mehri
authors: M
authors: Sirous
authors: Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
authors: Mohammad Esmaeil
authors: ME
authors: Akbari
keywords: Breast neoplasm; Image enhancement; Mammography; Wavelet transform
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