• DocumentCode
    3694509
  • Title

    Breast ultrasound automated ROI segmentation with region growing

  • Author

    Lay-Khoon Lee;Siau-Chuin Liew

  • Author_Institution
    Kolej Kediaman 1, Lebuhraya Tun Razak, 26300 Gambang, Kuantan, Pahang Darul Makmur, University Malaysia Pahang, Malaysia
  • fYear
    2015
  • Firstpage
    177
  • Lastpage
    182
  • Abstract
    Image segmentation is an important technology used in different areas ranging from image processing to image analysis. One of the simplest methods for image segmentation that is widely implemented in medical images is the region growing method. Current researches mostly focus on using the region growing method to automatically detect the presence of tumor in MRI (Magnetic Resonance) images instead of ultrasound images. In this paper, we present an algorithm to automatically detect tumors in ultrasound images. Inspired by SergeBeucher and Balasubramanian´s road segmentation algorithm, this paper will implement the road segmentation algorithm into medical image segmentation. Results show that, the road segmentation algorithm actually works on the segmentation of medical image. The dice coefficient was used to evaluate the accuracy of the algorithm, eventually getting a value of 0.988 ± 0.00147 as the mean and standard deviation. This value is significant, because the higher the DC value, the more accurate is the segmentation. Besides that, the DC value can use for future reference and comparison.
  • Keywords
    "Image segmentation","Ultrasonic imaging","Breast","Biomedical imaging","Cancer","Tumors","Feature extraction"
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Computer Systems (ICSECS), 2015 4th International Conference on
  • Type

    conf

  • DOI
    10.1109/ICSECS.2015.7333106
  • Filename
    7333106