Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/25583
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dc.titleA Set-based Hybrid Approach (SHA) for MRI segmentation
dc.contributor.authorLiu, J.
dc.contributor.authorLeong, T.-Y.
dc.contributor.authorChee, K.B.
dc.contributor.authorTan, B.P.
dc.contributor.authorShuter, B.
dc.contributor.authorWang, S.-C.
dc.date.accessioned2011-08-16T05:50:53Z
dc.date.available2011-08-16T05:50:53Z
dc.date.issued2006
dc.identifier.citationLiu, J., Leong, T.-Y., Chee, K.B., Tan, B.P., Shuter, B., Wang, S.-C. (2006). A Set-based Hybrid Approach (SHA) for MRI segmentation. 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06. ScholarBank@NUS Repository.
dc.identifier.isbn1424403421
dc.identifier.isbn9781424403424
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/25583
dc.description.abstractThis paper describes a new hybrid approach Set-Based Hybrid Approach (SHA) for Magnetic Resonance (MR) image segmentation by integrating two existing techniques, region-grow and threshold level set. To evaluate the proposed approach in performing real world image segmentation task, instead of using well-taken MR-images, we use real-life images collected in a hospital. Comparison of the performance between the two individual techniques and the new hybrid technique demonstrates the effectiveness of the latter. © 2006 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICARCV.2006.345358
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.contributor.departmentDIAGNOSTIC RADIOLOGY
dc.description.sourcetitle9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06
dc.identifier.isiutNOT_IN_WOS
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