Abnormal tissue detection of breast ultrasound image using combination of morphological technique

  • Authors:

  • Eko Supriyanto;Nor Saradatul Akmar Zulkifli;Mohsen Marvi Baigi;Nasrul Humaimi;Bustanur Rosidi

  • Affiliations:

  • Advanced Diagnostics and Progressive Human Care Research Group, Research Alliance Biotechnology, Faculty of Health Science and Biomedical Engineering, Universiti Teknologi Malaysia, Johor, Malaysi ...;Advanced Diagnostics and Progressive Human Care Research Group, Research Alliance Biotechnology, Faculty of Health Science and Biomedical Engineering, Universiti Teknologi Malaysia, Johor, Malaysi ...;Advanced Diagnostics and Progressive Human Care Research Group, Research Alliance Biotechnology, Faculty of Health Science and Biomedical Engineering, Universiti Teknologi Malaysia, Johor, Malaysi ...;Advanced Diagnostics and Progressive Human Care Research Group, Research Alliance Biotechnology, Faculty of Health Science and Biomedical Engineering, Universiti Teknologi Malaysia, Johor, Malaysi ...;Advanced Diagnostics and Progressive Human Care Research Group, Research Alliance Biotechnology, Faculty of Health Science and Biomedical Engineering, Universiti Teknologi Malaysia, Johor, Malaysi ...

  • Venue:
  • Proceedings of the 15th WSEAS international conference on Computers
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Breast cancer is the most common killer in women worldwide, which is originating from breast tissue. Early detection of breast cancer plays an important role in its therapy. Existing breast cancer detection method like ultrasound imaging can not be used at all ages, also quality of obtained images affected by speckle noise. Thus, it is essential to introduce new method to overcome these problems.This paper proposes an approach of detecting abnormal tissue in ultrasound breast image. The objective is to detect the abnormal tissue such as cyst or tumor inside breast tissues using image segmentation and combination of morphological technique. Image was processed using threshold segmentation method followed by dilation and erosion. The region of abnormalities tissue were found and has been differentiating from other tissue through several step of method applied. Besides, the same method was applied to the other different type of breast abnormalities tissue and the necessary result was obtained. The finding results show that this method can be used for early detection of breast cancer since it can detect several types of abnormalities in breast tissues.