File Download
Supplementary
-
Citations:
- Appears in Collections:
Conference Paper: Semi-automatic tumor boundary detection in MR image sequences
Title | Semi-automatic tumor boundary detection in MR image sequences |
---|---|
Authors | |
Issue Date | 2001 |
Publisher | IEEE. |
Citation | International Symposium on Intelligent Multimedia, Video and Speech Processing, Hong Kong, China, 2-4 May 2001, p. 28-31 How to Cite? |
Abstract | The authors present a semi-automatic approach for the detection of tumor boundary in MR image sequences. An initial slice with an obvious tumor is selected from the image sequence. The tumor is roughly segmented using fuzzy c-means algorithm and its boundary can be further refined by region and contour deformation. For the rest of the slices, the initial plan applied for each slice is extracted from the resulting boundary of the previous slice. The tumor boundary is located using region and contour deformation. Performance of our approach is evaluated on the MR image sequence. Comparisons with manual tracing show the accuracy and effectiveness of our approach. |
Persistent Identifier | http://hdl.handle.net/10722/46219 |
ISBN |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Law, AKW | en_HK |
dc.contributor.author | Zhu, H | en_HK |
dc.contributor.author | Chan, BCB | en_HK |
dc.contributor.author | Lu, PP | en_HK |
dc.contributor.author | Lam, FK | en_HK |
dc.contributor.author | Chan, FHY | en_HK |
dc.date.accessioned | 2007-10-30T06:45:03Z | - |
dc.date.available | 2007-10-30T06:45:03Z | - |
dc.date.issued | 2001 | en_HK |
dc.identifier.citation | International Symposium on Intelligent Multimedia, Video and Speech Processing, Hong Kong, China, 2-4 May 2001, p. 28-31 | en_HK |
dc.identifier.isbn | 962-85766-2-3 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/46219 | - |
dc.description.abstract | The authors present a semi-automatic approach for the detection of tumor boundary in MR image sequences. An initial slice with an obvious tumor is selected from the image sequence. The tumor is roughly segmented using fuzzy c-means algorithm and its boundary can be further refined by region and contour deformation. For the rest of the slices, the initial plan applied for each slice is extracted from the resulting boundary of the previous slice. The tumor boundary is located using region and contour deformation. Performance of our approach is evaluated on the MR image sequence. Comparisons with manual tracing show the accuracy and effectiveness of our approach. | en_HK |
dc.format.extent | 402079 bytes | - |
dc.format.extent | 13817 bytes | - |
dc.format.extent | 8841 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.format.mimetype | text/plain | - |
dc.format.mimetype | text/plain | - |
dc.language | eng | en_HK |
dc.publisher | IEEE. | en_HK |
dc.rights | ©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
dc.title | Semi-automatic tumor boundary detection in MR image sequences | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.openurl | http://library.hku.hk:4550/resserv?sid=HKU:IR&issn=962-85766-2-3&volume=&spage=28&epage=31&date=2001&atitle=Semi-automatic+tumor+boundary+detection+in+MR+image+sequences | en_HK |
dc.description.nature | published_or_final_version | en_HK |
dc.identifier.doi | 10.1109/ISIMP.2001.925322 | en_HK |
dc.identifier.hkuros | 58534 | - |