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|Title:||An improved shape determinative slice determination method for patient-specific modeling of facial anatomical structure|
|Keywords:||Facial anatomical structure|
|Citation:||Ng, H.P.,Liu, J.,Huang, S.,Ong, S.H.,Foong, K.W.C.,Goh, P.S.,Nowinski, W.L. (2008). An improved shape determinative slice determination method for patient-specific modeling of facial anatomical structure. International Journal of Computer Assisted Radiology and Surgery 3 (3-4) : 221-230. ScholarBank@NUS Repository.|
|Abstract:||Objective: In planning of maxillofacial surgeries, analysis and quantification of facial anatomical structures are carried out. At CARS 2007, we proposed a method to determine shape determinative slices, which captures the salient features of the shape of the 3D anatomical structure, to facilitate building of patient-specific models and rapid quantification. The accuracy of the built models was satisfactory. Here we propose an improved method that improves the accuracy of the built models through automatic refinement on the choice of the shape determinative slices by incorporating information from test dataset. Materials and methods: Twelve magnetic resonance imaging (MRI) datasets from adult volunteers, whose identities are anonymized, are used in this study. The earlier proposed method is used to determine the initial normalized locations of the shape determinative slices from training datasets. Given a test data, 2D automatic segmentations were performed on these initial locations and their neighboring slices. An area-based criterion is then used to refine the choice of the shape determinative slice. Results and conclusions: A total of 24 (12 left and 12 right muscles) patient-specific models were built from the shape determinative slices determined by our proposed method. The average overlap index achieved is about 87%. The models built from the shape determinative slices determined using the improved method have improvement in accuracy of up to 4.2%. The process of selecting the new shape determinative slices is automatic and the results indicate that the proposed method is effective. © CARS 2008.|
|Source Title:||International Journal of Computer Assisted Radiology and Surgery|
|Appears in Collections:||Staff Publications|
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