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Article: Automatic detection and classification of nasopharyngeal carcinoma on PET/CT with support vector machine

TitleAutomatic detection and classification of nasopharyngeal carcinoma on PET/CT with support vector machine
Authors
KeywordsComputer automatic diagnosis
Nasopharyngeal carcinoma
Pet/CT
Support vector machine
Issue Date2012
PublisherSpringer Berlin / Heidelberg
Citation
International Journal Of Computer Assisted Radiology And Surgery, 2012, v. 7 n. 4, p. 635-646 How to Cite?
AbstractPurpose: Positron emission tomography/computed tomography (PET/CT) has established values for imaging of head and neck cancers, including the nasopharyngeal carcinoma (NPC), utilizing both morphologic and functional information. In this paper, we introduce a computerized system for automatic detection of NPC, targeting both the primary tumor and regional nodal metastasis, on PET/CT. Methods: Candidate lesions were extracted based on the features from both PET and CT images and a priori knowledge of anatomical features and subsequently classified by a support vector machine algorithm. The system was validated with 25 PET/CT examinations from 10 patients suffering from NPC. Lesions manually contoured by experienced radiologists were used as the gold standard. Results: Results showed that the system successfully identified all 53 hypermetabolic lesions larger than 1 cm in size and excluded normal physiological uptake in brown fat, muscles, bone marrow, brain, and salivary glands. Conclusion: The system combined both imaging features and a priori clinical knowledge for classification between pathological and physiological uptake. Preliminary results showed that the system was highly accurate and promising for adoption in clinical use. © The Author(s) 2011.
Persistent Identifierhttp://hdl.handle.net/10722/147097
ISSN
2015 Impact Factor: 1.827
2015 SCImago Journal Rankings: 0.539
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWu, Ben_HK
dc.contributor.authorKhong, PLen_HK
dc.contributor.authorChan, Ten_HK
dc.date.accessioned2012-05-25T07:50:41Z-
dc.date.available2012-05-25T07:50:41Z-
dc.date.issued2012en_HK
dc.identifier.citationInternational Journal Of Computer Assisted Radiology And Surgery, 2012, v. 7 n. 4, p. 635-646en_HK
dc.identifier.issn1861-6410en_HK
dc.identifier.urihttp://hdl.handle.net/10722/147097-
dc.description.abstractPurpose: Positron emission tomography/computed tomography (PET/CT) has established values for imaging of head and neck cancers, including the nasopharyngeal carcinoma (NPC), utilizing both morphologic and functional information. In this paper, we introduce a computerized system for automatic detection of NPC, targeting both the primary tumor and regional nodal metastasis, on PET/CT. Methods: Candidate lesions were extracted based on the features from both PET and CT images and a priori knowledge of anatomical features and subsequently classified by a support vector machine algorithm. The system was validated with 25 PET/CT examinations from 10 patients suffering from NPC. Lesions manually contoured by experienced radiologists were used as the gold standard. Results: Results showed that the system successfully identified all 53 hypermetabolic lesions larger than 1 cm in size and excluded normal physiological uptake in brown fat, muscles, bone marrow, brain, and salivary glands. Conclusion: The system combined both imaging features and a priori clinical knowledge for classification between pathological and physiological uptake. Preliminary results showed that the system was highly accurate and promising for adoption in clinical use. © The Author(s) 2011.en_HK
dc.languageengen_US
dc.publisherSpringer Berlin / Heidelbergen_US
dc.relation.ispartofInternational Journal of Computer Assisted Radiology and Surgeryen_HK
dc.rightsThe Author(s)en_US
dc.rightsCreative Commons: Attribution 3.0 Hong Kong Licenseen_US
dc.subjectComputer automatic diagnosisen_HK
dc.subjectNasopharyngeal carcinomaen_HK
dc.subjectPet/CTen_HK
dc.subjectSupport vector machineen_HK
dc.titleAutomatic detection and classification of nasopharyngeal carcinoma on PET/CT with support vector machineen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://www.springerlink.com/link-out/?id=2104&code=T6K770373U576944&MUD=MPen_US
dc.identifier.emailKhong, PL: plkhong@hkucc.hku.hken_HK
dc.identifier.emailChan, T: taochan@hku.hken_HK
dc.identifier.authorityKhong, PL=rp00467en_HK
dc.identifier.authorityChan, T=rp00289en_HK
dc.description.naturepublished_or_final_versionen_US
dc.identifier.doi10.1007/s11548-011-0669-yen_HK
dc.identifier.pmid22215412-
dc.identifier.scopuseid_2-s2.0-84865788159en_HK
dc.identifier.hkuros206690-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84865788159&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume7en_HK
dc.identifier.issue4en_HK
dc.identifier.spage635en_HK
dc.identifier.epage646en_HK
dc.identifier.eissn1861-6429en_US
dc.identifier.isiWOS:000306219300012-
dc.publisher.placeGermanyen_HK
dc.description.otherSpringer Open Choice, 25 May 2012en_US
dc.identifier.scopusauthoridWu, B=55468218600en_HK
dc.identifier.scopusauthoridKhong, PL=7006693233en_HK
dc.identifier.scopusauthoridChan, T=35147479300en_HK
dc.identifier.citeulike10207344-

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