Concept detection in longitudinal brain mr images using multi-modal cues

Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Volumn , Issue , 2009, Pages 418-421

  Caban, Jesus J ^a   Lee, Noah ^b   Ebadollahi, Shahram ^c   Laine, Andrew F ^b   Kender, John R ^c  

^a UNIVERSITY OF MARYLAND BALTIMORE COUNTY   (United States)

^b Department of Earth and Environmental Sciences   (United States)

^c IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

Brain tumors; Computer aided diagnosis systems; Longitudinal image sets; Multi modal images; Semi supervised learning; Supervised learning

Indexed keywords

BRAIN TUMORS; COMPUTER-AIDED DIAGNOSIS SYSTEMS; LONGITUDINAL IMAGE SETS; MULTI-MODAL IMAGES; SEMI-SUPERVISED LEARNING;

COMPUTER AIDED DIAGNOSIS; EDUCATION; MACROS; MEDICAL IMAGING; ONCOLOGY; SUPERVISED LEARNING; TUMORS;

IMAGE PROCESSING;

EID: 70449339873     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2009.5193073     Document Type: Conference Paper

References (4)

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2. Noah Lee, Jesus J. Caban, Shahram Ebadollahi, and Andrew F. Laine, "Interactive segmentation in multi-modal medical imagery using a bayesian transductive learning approach", SPIE Medical Imaging, vol. 7260, 2009.
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4. Hanchuan Peng, Fuhui Long, and Chris Ding, "Feature selection based on mutual information: criteria of maxdependency, max-relevance, and min-redundancy", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 8, pp. 1226-1238, 2005.