• DocumentCode
    1589098
  • Title

    Medical Images Edge Detection Based on Mathematical Morphology

  • Author

    Yu-qian, Zhao ; Wei-hua, Gui ; Zhen-cheng, Chen ; Jing-tian, Tang ; Ling-yun, Li

  • Author_Institution
    Inst. of Biomed. Eng., Central South Univ., Changsha
  • fYear
    2006
  • Firstpage
    6492
  • Lastpage
    6495
  • Abstract
    Medical images edge detection is an important work for object recognition of the human organs and it is an important pre-processing step in medical image segmentation and 3D reconstruction. Conventionally, edge is detected according to some early brought forward algorithms such as gradient-based algorithm and template-based algorithm, but they are not so good for noise medical image edge detection. In this paper, basic mathematical morphological theory and operations are introduced at first, and then a novel mathematical morphological edge detection algorithm is proposed to detect the edge of lungs CT image with salt-and-pepper noise. The experimental results show that the proposed algorithm is more efficient for medical image denoising and edge detection than the usually used template-based edge detection algorithms and general morphological edge detection algorithms
  • Keywords
    computerised tomography; edge detection; image denoising; lung; medical image processing; object recognition; 3D reconstruction; CT image; edge detection; forward algorithms; gradient-based algorithm; human organs; lungs; mathematical morphology; medical image denoising; medical image segmentation; medical images; object recognition; salt-and-pepper noise; template-based algorithm; Biomedical imaging; Computed tomography; Humans; Image denoising; Image edge detection; Image reconstruction; Image segmentation; Lungs; Morphology; Object recognition; Medical image; denoising; edge detection; mathematical morphology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1615986
  • Filename
    1615986