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Published in:

Volume 7 Issue 7
July-2020
eISSN: 2349-5162

Unique Identifier

JETIR2007316

Page Number

159-162

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Title

Method of detecting micro-calcification clusters using contourlet transform and PCNN

ISSN

2349-5162

Cite This Article

"Method of detecting micro-calcification clusters using contourlet transform and PCNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 7, page no.159-162, July-2020, Available :http://www.jetir.org/papers/JETIR2007316.pdf

Abstract

Mammography analysis is an effective technology for early detection of breast cancer. Micro-calcification clusters (MCs) are a vital indicator of breast cancer, so detection of MCs plays an important role in computer aided detection (CAD) system, this paper proposes a new hybrid method to improve MCs detection rate in mammograms. Methods: The proposed method comprises three main steps: firstly, remove label and pectoral muscle adopting the largest connected region marking and region growing method, and enhance MCs using the combination of double top-hat transform and grayscale-adjustment function; secondly, remove noise and other interference information, and retain the significant information by modifying the contourlet coefficients using nonlinear function; thirdly, we use the non-linking simplified pulse-coupled neural network to detect MCs. Results: In our work, we choose 118 mammograms including 38 mammograms with micro-calcification clusters and 80 mammograms without micro-calcification to demonstrate our algorithm separately from two open and common database including the MIAS and JSMIT; and we achieve the higher specificity of 94.7%, sensitivity of 96.3%, AUC of 97.0%, accuracy of 95.8%, MCC of 90.4%, MCC-PS of 61.3% and CEI of 53.5%, these promising results clearly demonstrate that the proposed approach outperforms the current state-of-the-art algorithms. In addition, this method is verified on the 20 mammograms from the People’s Hospital of Gansu Province, the detection results reveal that our method can accurately detect the calcifications in clinical application.

Key Words

Mammography,Micro-calcification clusters, Contourlet Transform, Simplified pulse-coupled neural network(SPCNN)

Cite This Article

"Method of detecting micro-calcification clusters using contourlet transform and PCNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 7, page no. pp159-162, July-2020, Available at : http://www.jetir.org/papers/JETIR2007316.pdf

Publication Details

Published Paper ID: JETIR2007316
Registration ID: 235456
Published In: Volume 7 | Issue 7 | Year July-2020
DOI (Digital Object Identifier):
Page No: 159-162
ISSN Number: 2349-5162

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Cite This Article

"Method of detecting micro-calcification clusters using contourlet transform and PCNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 7, page no. pp159-162, July-2020, Available at : http://www.jetir.org/papers/JETIR2007316.pdf




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