• DocumentCode
    2893302
  • Title

    A Morphological Segmentation Based Features for Brain MRI Retrieval

  • Author

    Ingole, Prashant V. ; Kulat, Kishore D.

  • Author_Institution
    G.H. Raisoni Coll. of Eng. & Manage., Amravati, India
  • fYear
    2011
  • fDate
    18-20 Nov. 2011
  • Firstpage
    210
  • Lastpage
    214
  • Abstract
    Retrieval of domain specific images is an important research area. Human brain MR Image retrieval of similar MR Images is an important application in Radiology field of medical diagnostics. Morphological segmentation is proposed for highlighting and extraction of the region based features of human brain T2 - weighted MR Images. Further fuzzy representation of these features and its use in retrieval of brain MRI is demonstrated in this paper. Segmentation results show a marked improvement in the quality of segmentation as compared to Fuzzy c-means clustering method and confirmed with manual segmentation. Further its use in retrieval has also found to give better retrieval results in terms of precision and average rank.
  • Keywords
    biomedical MRI; brain; feature extraction; fuzzy set theory; image representation; image retrieval; image segmentation; mathematical morphology; radiology; brain MRI; feature extraction; fuzzy set theory; image representation; image retrieval; medical diagnostics; morphological segmentation; radiology; Biomedical imaging; Brain; Feature extraction; Humans; Image segmentation; Magnetic resonance imaging; Content-Based Image Retrieval(CBIR); Magnetic Resonance Image (MRI); Morphological Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Trends in Engineering and Technology (ICETET), 2011 4th International Conference on
  • Conference_Location
    Port Louis
  • ISSN
    2157-0477
  • Print_ISBN
    978-1-4577-1847-2
  • Type

    conf

  • DOI
    10.1109/ICETET.2011.12
  • Filename
    6120584