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
Link To Document :
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