Segmentation of medical images using geo-theoretic distance matrix in fuzzy clustering
Pham, Tuan D., Eisenblätter, Uwe, Golledge, Jonathan, Baune, Bernhard T., and Berger, Klaus (2010) Segmentation of medical images using geo-theoretic distance matrix in fuzzy clustering. Proceedings of the 16th IEEE International Conference on Image Processing (ICIP). 16th IEEE International Conference on Image Processing (ICIP) , 7-10 November 2009, Cairo, Egypt , pp. 3369-3372.
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Investigation on novel methods for extracting objects of interest in medical images has been an important and challenging area of research in image analysis. In particular, medical images are highly spatially correlated and subject to fuzzy distribution of pixels, we present in this paper a new algorithm for medical image segmentation with special reference to abdominal aortic aneurysm and degraded human brain imaging. Development of the new algorithm is based on the implementation of the theoretic distance matrix with spatial semi-variances.
|Item Type:||Conference Item (Refereed Research Paper - E1)|
|Keywords:||CT imaging; MRI; medical image segmentation; fuzzy c-means; semi-variance|
|FoR Codes:||11 MEDICAL AND HEALTH SCIENCES > 1103 Clinical Sciences > 110320 Radiology and Organ Imaging @ 40%|
11 MEDICAL AND HEALTH SCIENCES > 1102 Cardiovascular Medicine and Haematology > 110201 Cardiology (incl Cardiovascular Diseases) @ 20%
02 PHYSICAL SCIENCES > 0299 Other Physical Sciences > 029903 Medical Physics @ 40%
|SEO Codes:||92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920103 Cardiovascular System and Diseases @ 20%|
92 HEALTH > 9202 Health and Support Services > 920203 Diagnostic Methods @ 80%
|Deposited On:||04 May 2010 13:18|
|Last Modified:||10 Aug 2011 10:46|
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