Please use this identifier to cite or link to this item: https://doi.org/10.1007/s11548-007-0073-9
Title: Segmentation of the temporalis muscle from MR data
Authors: Ng, H.P.
Hu, Q.M.
Ong, S.H. 
Foong, K.W.C. 
Goh, P.S.
Liu, J.
Nowinski, W.L.
Keywords: Masticatory muscle
MRI
Segmentation
Temporalis
Issue Date: 2007
Source: Ng, 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
Abstract: Objective: 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.
Source Title: International Journal of Computer Assisted Radiology and Surgery
URI: http://scholarbank.nus.edu.sg/handle/10635/57351
ISSN: 18616410
DOI: 10.1007/s11548-007-0073-9
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