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Article: Automated analysis of nerve-cell images using active contour models

TitleAutomated analysis of nerve-cell images using active contour models
Authors
KeywordsBrain
Cells
Computer simulation
Image analysis
Mathematical transformations
Neurophysiology
Physiological models
Issue Date1996
PublisherIEEE
Citation
Ieee Transactions On Medical Imaging, 1996, v. 15 n. 3, p. 353-368 How to Cite?
AbstractThe number of nerve fibers (axons) in a nerve, the axun size, and shape can all be important neuroaiiatoiiiical features in understanding different aspects of nerves in the brain. However, the number of axons in a nerve is typically in the order of tens of thousands and a study of a particular aspect of the nerve often involves many nerves. Potentially meaningful studies are often prohibited by the huge number involved when manual measurements have to be employed. A method that automates the analysis of axons from electronmicrographic images is presented. It begins with a rough identification of all the axon centers by use of an elliptical Hough transform procedure. Boundaries of each axons are then extracted based on active contour model, or snakes, approach where physical properties of the axons and the given image data are used in an optimization scheme to guide the snakes to converge to axon boundaries for accurate sheath measurement. However, false axon detection is still common due to poor image quality and the presence of other irrelevant cell features, thus a conflict resolution scheme is developed to eliminate false axons to further improve the performance of detection. The developed method has been tested on a number of nerve images and its results are presented. © 1996 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/65543
ISSN
2015 Impact Factor: 3.756
2015 SCImago Journal Rankings: 1.941
References

 

DC FieldValueLanguage
dc.contributor.authorFok, YLen_HK
dc.contributor.authorChan, JCKen_HK
dc.contributor.authorChin, RTen_HK
dc.date.accessioned2010-08-31T07:15:15Z-
dc.date.available2010-08-31T07:15:15Z-
dc.date.issued1996en_HK
dc.identifier.citationIeee Transactions On Medical Imaging, 1996, v. 15 n. 3, p. 353-368en_HK
dc.identifier.issn0278-0062en_HK
dc.identifier.urihttp://hdl.handle.net/10722/65543-
dc.description.abstractThe number of nerve fibers (axons) in a nerve, the axun size, and shape can all be important neuroaiiatoiiiical features in understanding different aspects of nerves in the brain. However, the number of axons in a nerve is typically in the order of tens of thousands and a study of a particular aspect of the nerve often involves many nerves. Potentially meaningful studies are often prohibited by the huge number involved when manual measurements have to be employed. A method that automates the analysis of axons from electronmicrographic images is presented. It begins with a rough identification of all the axon centers by use of an elliptical Hough transform procedure. Boundaries of each axons are then extracted based on active contour model, or snakes, approach where physical properties of the axons and the given image data are used in an optimization scheme to guide the snakes to converge to axon boundaries for accurate sheath measurement. However, false axon detection is still common due to poor image quality and the presence of other irrelevant cell features, thus a conflict resolution scheme is developed to eliminate false axons to further improve the performance of detection. The developed method has been tested on a number of nerve images and its results are presented. © 1996 IEEE.en_HK
dc.languageengen_HK
dc.publisherIEEEen_HK
dc.relation.ispartofIEEE Transactions on Medical Imagingen_HK
dc.subjectBrainen_HK
dc.subjectCellsen_HK
dc.subjectComputer simulationen_HK
dc.subjectImage analysisen_HK
dc.subjectMathematical transformationsen_HK
dc.subjectNeurophysiologyen_HK
dc.subjectPhysiological modelsen_HK
dc.titleAutomated analysis of nerve-cell images using active contour modelsen_HK
dc.typeArticleen_HK
dc.identifier.emailChin, RT: rchin@hku.hken_HK
dc.identifier.authorityChin, RT=rp01300en_HK
dc.description.naturelink_to_subscribed_fulltexten_HK
dc.identifier.doi10.1109/42.500144en_HK
dc.identifier.scopuseid_2-s2.0-0030169990en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0030169990&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume15en_HK
dc.identifier.issue3en_HK
dc.identifier.spage353en_HK
dc.identifier.epage368en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridFok, YL=7003587778en_HK
dc.identifier.scopusauthoridChan, JCK=7403286662en_HK
dc.identifier.scopusauthoridChin, RT=7102445426en_HK
dc.identifier.citeulike9637660-

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