Contrast Enhancement of Mammograms for Rapid Detection of Microcalcification Clusters

Authors

  • Alireza Karimian Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran
  • Hajar Moradmand Department of Biomedical-Radiation Engineering, Amirkabir University of Technology, Tehran, Iran
  • Mehri Sirous Department of Radiology, Isfahan University of Medical Sciences, Isfahan, Iran
  • Saeed Setayeshi Department of Biomedical-Radiation Engineering, Amirkabir University of Technology, Tehran, Iran
Abstract:

Introduction Breast cancer is one of the most common types of cancer among women.  Early detection of breast cancer is the key to reducing the associated mortality rate. The presence of microcalcifications clusters (MCCs) is one of the earliest signs of breast cancer. Due to poor imaging contrast of mammograms and noise contamination, radiologists may overlook some diagnostic signs, specially the presence of MCCs. In order to improve cancer detection, image enhancement methods are often used to aid radiologists. In this paper, a new enhancement method was presented for the accurate and early detection of MCCs in mammograms. Materials and Methods The proposed system consisted of four main steps including: 1) image scaling;2) breast region segmentation;3) noise cancellation using a filter, which is sensitive to MCCs; and 4) contrast enhancement of mammograms using Contrast-Limited Adaptive Histogram Equalization (CLAHE) and wavelet transform. To evaluate this method, 120 clinical mammograms were used. Results To evaluate the performance of the image enhancement algorithm, contrast improvement index (CII) was used. The proposed enhancement method in this research achieved the highest CII in comparison with other methods applied in this study. The Validity of the results was confirmed by an expert radiologist through visual inspection. Conclusion Detection of MCCs significantly improved in contrast-enhanced mammograms. The proposed method could be helpful for radiologists to easily detect MCCs; it could also decrease the number of biopsies and reduce the frequency of clinical misdiagnosis. Moreover, it could be useful prior to segmentation or classification stages.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

contrast enhancement of mammograms for rapid detection of microcalcification clusters

introduction breast cancer is one of the most common types of cancer among women.  early detection of breast cancer is the key to reducing the associated mortality rate. the presence of microcalcifications clusters (mccs) is one of the earliest signs of breast cancer. due to poor imaging contrast of mammograms and noise contamination, radiologists may overlook some diagnostic signs, specially t...

full text

Detection of Microcalcification Clusters in Mammograms Using Curvelet Transform

In this paper we present a new approach for computer aided detection of microcalcifications (MC) clusters in mammograms. The proposed method is done in two stages; the first stage is a preprocessing with histogram, in the second stage the ability of these filtered images in detecting microcalcification is done using the Curvelet Transform. The proposed method is applied to a database of 10 dens...

full text

Fractal-Based Detection of Microcalcification Clusters in Digital Mammograms

In this paper, a novel method for edge detection of microcalcification clusters in mammogram images is presented using the concept of Fractal Dimension and Hurst co-efficient that enables to locate the microcalcifications in the mammograms. This technique detects the edges accurately than the ones obtained by the conventional Sobel method. Generally, Sobel method detects the edges of the region...

full text

Hybrid Microcalcification Detection In Mammograms

This paper presents a combined system for detecting microcalcifications in mammographic images. The proposed approach analyses the mammograms using the parallel combination of two methods. One of the methods is a heuristic approach that is based on features used by humans to descript microcalcifications. Second approach applies a hierarchical neural structure trained on images already interpret...

full text

Comparing Methods for segmentation of Microcalcification Clusters in Digitized Mammograms

The appearance of microcalcifications in mammograms is one of the early signs of breast cancer. So, early detection of microcalcification clusters (MCCs) in mammograms can be helpful for cancer diagnosis and better treatment of breast cancer. In this paper a computer method has been proposed to support radiologists in detection MCCs in digital mammography. First, in order to facilitate and impr...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 11  issue Issue 2,3

pages  260- 269

publication date 2014-08-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023