File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/ICIP.2010.5650763
- Scopus: eid_2-s2.0-78651095236
- WOS: WOS:000287728001040
- Find via
Supplementary
- Citations:
- Appears in Collections:
Conference Paper: Automatic detection of malignant prostatic gland units in cross-sectional microscopic images
Title | Automatic detection of malignant prostatic gland units in cross-sectional microscopic images |
---|---|
Authors | |
Keywords | Classification Histological Images Prostate glands Segmentation |
Issue Date | 2010 |
Publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000349 |
Citation | The 17th IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, China, 26-29 September 2010. In Proceedings of the 17th ICIP, 2010, p. 1057-1060 How to Cite? |
Abstract | Prostate cancer is the second most frequent cause of cancer deaths among men in the US. In the most reliable screening method, histological images from a biopsy are examined under a microscope by pathologists. In an early stage of prostate cancer, only relatively few gland units in a large region become malignant. Discovering such sparse malignant gland units using a microscope is a labor-intensive and error-prone task for pathologists. In this paper, we develop effective image segmentation and classification methods for automatic detection of malignant gland units in microscopic images. Both segmentation and classification methods are based on carefully designed feature descriptors, including color histograms and texton co-occurrence tables. © 2010 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/139999 |
ISSN | 2020 SCImago Journal Rankings: 0.315 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Xia, T | en_HK |
dc.contributor.author | Yu, Y | en_HK |
dc.contributor.author | Hua, J | en_HK |
dc.date.accessioned | 2011-09-23T06:04:31Z | - |
dc.date.available | 2011-09-23T06:04:31Z | - |
dc.date.issued | 2010 | en_HK |
dc.identifier.citation | The 17th IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, China, 26-29 September 2010. In Proceedings of the 17th ICIP, 2010, p. 1057-1060 | en_HK |
dc.identifier.issn | 1522-4880 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/139999 | - |
dc.description.abstract | Prostate cancer is the second most frequent cause of cancer deaths among men in the US. In the most reliable screening method, histological images from a biopsy are examined under a microscope by pathologists. In an early stage of prostate cancer, only relatively few gland units in a large region become malignant. Discovering such sparse malignant gland units using a microscope is a labor-intensive and error-prone task for pathologists. In this paper, we develop effective image segmentation and classification methods for automatic detection of malignant gland units in microscopic images. Both segmentation and classification methods are based on carefully designed feature descriptors, including color histograms and texton co-occurrence tables. © 2010 IEEE. | en_HK |
dc.language | eng | en_US |
dc.publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000349 | en_HK |
dc.relation.ispartof | Proceedings of the International Conference on Image Processing, ICIP 2010 | en_HK |
dc.rights | ©2010 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.subject | Classification | en_HK |
dc.subject | Histological Images | en_HK |
dc.subject | Prostate glands | en_HK |
dc.subject | Segmentation | en_HK |
dc.title | Automatic detection of malignant prostatic gland units in cross-sectional microscopic images | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.email | Yu, Y:yzyu@cs.hku.hk | en_HK |
dc.identifier.authority | Yu, Y=rp01415 | en_HK |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1109/ICIP.2010.5650763 | en_HK |
dc.identifier.scopus | eid_2-s2.0-78651095236 | en_HK |
dc.identifier.hkuros | 194319 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-78651095236&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.spage | 1057 | en_HK |
dc.identifier.epage | 1060 | en_HK |
dc.identifier.isi | WOS:000287728001040 | - |
dc.publisher.place | United States | en_HK |
dc.description.other | The 17th IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, China, 26-29 September 2010. In Proceedings of the 17th ICIP, 2010, p. 1057-1060 | - |
dc.identifier.scopusauthorid | Xia, T=35876042700 | en_HK |
dc.identifier.scopusauthorid | Yu, Y=8554163500 | en_HK |
dc.identifier.scopusauthorid | Hua, J=7102121257 | en_HK |
dc.identifier.issnl | 1522-4880 | - |