Please use this identifier to cite or link to this item: https://doi.org/10.1007/s11548-007-0073-9
DC FieldValue
dc.titleSegmentation of the temporalis muscle from MR data
dc.contributor.authorNg, H.P.
dc.contributor.authorHu, Q.M.
dc.contributor.authorOng, S.H.
dc.contributor.authorFoong, K.W.C.
dc.contributor.authorGoh, P.S.
dc.contributor.authorLiu, J.
dc.contributor.authorNowinski, W.L.
dc.date.accessioned2014-06-17T03:05:11Z
dc.date.available2014-06-17T03:05:11Z
dc.date.issued2007
dc.identifier.citationNg, H.P., Hu, Q.M., Ong, S.H., Foong, K.W.C., Goh, P.S., Liu, J., Nowinski, W.L. (2007). Segmentation of the temporalis muscle from MR data. International Journal of Computer Assisted Radiology and Surgery 2 (1) : 19-30. ScholarBank@NUS Repository. https://doi.org/10.1007/s11548-007-0073-9
dc.identifier.issn18616410
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/57351
dc.description.abstractObjective: A method for segmenting the temporalis from magnetic resonance (MR) images was developed and tested. The temporalis muscle is one of the muscles of mastication which plays a major role in the mastication system. Materials and methods: The temporalis region of interest (ROI) and the head ROI are defined in reference images, from which the spatial relationship between the two ROIs is derived. This relationship is used to define the temporalis ROI in a study image. Range-constrained thresholding is then employed to remove the fat, bone marrow and muscle tendon in the ROI. Adaptive morphological operations are then applied to first remove the brain tissue, followed by the removal of the other soft tissues surrounding the temporalis. Ten adult head MR data sets were processed to test this method. Results: Using five data sets each for training and testing, the method was applied to the segmentation of the temporalis in 25 MR images (five from each test set). An average overlap index κ of 90.2% was obtained. Applying a leave-one-out evaluation method, an average κ of 90.5% was obtained from 50 test images. Conclusion: A method for segmenting the temporalis from MR images was developed and tested on in vivo data sets. The results show that there is consistency between manual and automatic segmentations. © CARS 2007.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s11548-007-0073-9
dc.sourceScopus
dc.subjectMasticatory muscle
dc.subjectMRI
dc.subjectSegmentation
dc.subjectTemporalis
dc.typeArticle
dc.contributor.departmentPREVENTIVE DENTISTRY
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1007/s11548-007-0073-9
dc.description.sourcetitleInternational Journal of Computer Assisted Radiology and Surgery
dc.description.volume2
dc.description.issue1
dc.description.page19-30
dc.identifier.isiut000208989400003
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.