A system for computer aided diagnosis of breast cancer based on mass analysis

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3 Citations (Scopus)

Abstract

This paper discusses the method to automatic mass segmentation and analysis of mammogram for classification of benign or malignant tumor. The identification process is started with image enhancement through cropping to remove artifacts, then followed by increasing the contrast through Contrast Limited Adaptive Histogram Equalization (CLAHE). The selection of mass candidate is carried out through 2 phases: marking the suspected mass area (Region of Interest - ROI) using adaptive thresholding p-tile technique and marking the connected components, and texture feature extracting on the ROI to classify whether the ROI is mass or non-mass. The texture feature extraction is performed by Grey Level Co-occurrence Matrices (GLCM) set up on four different directions, 0°, 45°, 90°, and 135°. The application captures a mammogram image as an input and displays the presence of suspicious mass and its margin, if any. The segmented mass is analyzed based on its shape and margin. Thereafter, these information can be used by physicians to classify the type of tumor and to decide whether a biopsy is necessary. The application is evaluated using the mammogram data from Mammographic Image Analysis Society (MIAS). The MIAS data consist of 207 images of normal breast, 64 benign, and 51 malignant. 85 mammograms of MIAS data have mass. It is tested using Mammogram from Picture Archive Communication System (PACS) Pertamina hospital. Based on the study conducted, the algorithm developed step by step can localize the suspected area therefore it is able to detect the shape and the edge of mass on mammogram.

Original languageEnglish
Title of host publicationProceedings of 2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems, ROBIONETICS 2013
Pages247-253
Number of pages7
DOIs
Publication statusPublished - 1 Dec 2013
Event2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems, ROBIONETICS 2013 - Yogyakarta, Indonesia
Duration: 25 Nov 201327 Nov 2013

Publication series

NameProceedings of 2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems, ROBIONETICS 2013

Conference

Conference2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems, ROBIONETICS 2013
Country/TerritoryIndonesia
CityYogyakarta
Period25/11/1327/11/13

Keywords

  • Breast cancer
  • Edge detection
  • Gray Level Co-occurrence Matrix (GLCM)
  • Region Of Interest (ROI)

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