Yue Zhou1, Ju-Peng Li1, Wen-Chao Lv1, Ruo-Han Ma2, Gang Li2. 1. 1 Signal and image processing laboratory, School of Electronic Information Engineering, Beijing Jiao tong University , Beijing , China. 2. 2 Department of Oral and Maxillofacial Radiology, Peking University, School and Hospital of Stomatology , Beijing , China.
Abstract
OBJECTIVES: A method was introduced for three-dimensional (3D) cone-beamCT (CBCT) images registration of temporomandibular joint (TMJ). This study aimed to provide quantitative and qualitative analysis of TMJ bone changes in two-dimensional (2D) and 3D and to provide the technique for computer-aided diagnosis of temporomandibular joint disorders in the future. METHODS: 10 TMJ samples of six patients were obtained from Peking University Hospital of Stomatology. Four of the six patients imaged bilateral TMJs and the other two patients only imaged unilateral TMJ. Each sample consisted of two images from the same TMJ taken at different times. First, condyle and skull base were segmented semi-automatically for 3D model reconstruction. Then the segmented condyle and skull base were registered separately. Registration process can be divided into two processes of rough registration and fine registration. Rough registration step was achieved by selecting corresponding points manually and initialized fine registration. Condyle and skull base were fine registered by minimizing mean square error of condyle (MSEcondyle) and skull base (MSEskull) respectively. Qualitative assessment of osseous component changes utilized 2D color-fused model and 3D surface-fused model and quantitative analyses the convergence of this method used the mean square error of the model (MSEmodel). Independent repeated experiments were carried out to test the stability of our 3D registration method. RESULTS: Sufficiently alignment was achieved. Osseous abnormality and morphology changes were displayed using fusion model. MSEmodel of condylar registration and skull base registration declined 51.80% and 64.58% compared with that before registration. Quantitative analysis verified the stability of the method. CONCLUSIONS: The proposed method completed 3D TMJ registration for different physiological structure. The result of this method was accurate, reproducible and not relied on the experience of operators.
OBJECTIVES: A method was introduced for three-dimensional (3D) cone-beamCT (CBCT) images registration of temporomandibular joint (TMJ). This study aimed to provide quantitative and qualitative analysis of TMJ bone changes in two-dimensional (2D) and 3D and to provide the technique for computer-aided diagnosis of temporomandibular joint disorders in the future. METHODS: 10 TMJ samples of six patients were obtained from Peking University Hospital of Stomatology. Four of the six patients imaged bilateral TMJs and the other two patients only imaged unilateral TMJ. Each sample consisted of two images from the same TMJ taken at different times. First, condyle and skull base were segmented semi-automatically for 3D model reconstruction. Then the segmented condyle and skull base were registered separately. Registration process can be divided into two processes of rough registration and fine registration. Rough registration step was achieved by selecting corresponding points manually and initialized fine registration. Condyle and skull base were fine registered by minimizing mean square error of condyle (MSEcondyle) and skull base (MSEskull) respectively. Qualitative assessment of osseous component changes utilized 2D color-fused model and 3D surface-fused model and quantitative analyses the convergence of this method used the mean square error of the model (MSEmodel). Independent repeated experiments were carried out to test the stability of our 3D registration method. RESULTS: Sufficiently alignment was achieved. Osseous abnormality and morphology changes were displayed using fusion model. MSEmodel of condylar registration and skull base registration declined 51.80% and 64.58% compared with that before registration. Quantitative analysis verified the stability of the method. CONCLUSIONS: The proposed method completed 3D TMJ registration for different physiological structure. The result of this method was accurate, reproducible and not relied on the experience of operators.
Authors: S A Pawiro; P Markelj; F Pernus; C Gendrin; M Figl; C Weber; F Kainberger; I Nöbauer-Huhmann; H Bergmeister; M Stock; D Georg; H Bergmann; W Birkfellner Journal: Med Phys Date: 2011-03 Impact factor: 4.071