OBJECTIVE: This paper describes methods for the automatic atlas-based segmentation of bone structures of the hip, the automatic detection of anatomical point landmarks and the computation of orthopedic parameters to avoid the interactive, time-consuming pre-processing steps for the virtual planning of hip operations. METHODS: Based on the CT data of the Visible Human Data Sets, two three-dimensional atlases of the human pelvis have been built. The atlases consist of labeled CT data sets, 3D surface models of the separated structures and associated anatomical point landmarks. The atlas information is transferred to the patient data by a non-linear gray value-based registration algorithm. A surface-based registration algorithm was developed to detect the anatomical landmarks on the patient's bone structures. Furthermore, a software tool for the automatic computation of orthopedic parameters is presented. Finally, methods for an evaluation of the atlas-based segmentation and the atlas-based landmark detection are explained. RESULTS: A first evaluation of the presented atlas-based segmentation method shows the correct labeling of 98.5% of the bony voxels. The presented landmark detection algorithm enables the precise and reliable localization of orthopedic landmarks. The accuracy of the landmark detection is below 2.5 mm. CONCLUSION: The atlas-based segmentation of bone structures, the atlas-based landmark detection and the automatic computation of orthopedic measures are suitable to essentially reduce the time-consuming user interaction during the pre-processing of the CT data for the virtual three-dimensional planning of hip operations.
OBJECTIVE: This paper describes methods for the automatic atlas-based segmentation of bone structures of the hip, the automatic detection of anatomical point landmarks and the computation of orthopedic parameters to avoid the interactive, time-consuming pre-processing steps for the virtual planning of hip operations. METHODS: Based on the CT data of the Visible Human Data Sets, two three-dimensional atlases of the human pelvis have been built. The atlases consist of labeled CT data sets, 3D surface models of the separated structures and associated anatomical point landmarks. The atlas information is transferred to the patient data by a non-linear gray value-based registration algorithm. A surface-based registration algorithm was developed to detect the anatomical landmarks on the patient's bone structures. Furthermore, a software tool for the automatic computation of orthopedic parameters is presented. Finally, methods for an evaluation of the atlas-based segmentation and the atlas-based landmark detection are explained. RESULTS: A first evaluation of the presented atlas-based segmentation method shows the correct labeling of 98.5% of the bony voxels. The presented landmark detection algorithm enables the precise and reliable localization of orthopedic landmarks. The accuracy of the landmark detection is below 2.5 mm. CONCLUSION: The atlas-based segmentation of bone structures, the atlas-based landmark detection and the automatic computation of orthopedic measures are suitable to essentially reduce the time-consuming user interaction during the pre-processing of the CT data for the virtual three-dimensional planning of hip operations.
Authors: Michael Brehler; Gaurav Thawait; Jonathan Kaplan; John Ramsay; Miho J Tanaka; Shadpour Demehri; Jeffrey H Siewerdsen; Wojciech Zbijewski Journal: J Med Imaging (Bellingham) Date: 2019-06-19
Authors: Thomas M Deserno Né Lehmann; Heinz Handels; Klaus H Maier-Hein Né Fritzsche; Sven Mersmann; Christoph Palm; Thomas Tolxdorff; Gudrun Wagenknecht; Thomas Wittenberg Journal: Curr Med Imaging Rev Date: 2013-05
Authors: Maximilian C M Fischer; Sonja A G A Grothues; Juliana Habor; Matías de la Fuente; Klaus Radermacher Journal: Sci Rep Date: 2020-11-30 Impact factor: 4.379
Authors: Manas M Kawale; Gregory P Reece; Melissa A Crosby; Elisabeth K Beahm; Michelle C Fingeret; Mia K Markey; Fatima A Merchant Journal: Biomed Eng Comput Biol Date: 2013-07-02