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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/100/1595

Title: Computerized assessment of excessive femoral and tibial torsional deformation by 3D anatomical landmarks referencing
Authors: SUBBURAJ, K
RAVI, B
AGARWAL, MG
Keywords: anteversion
tomography
skeleton
Issue Date: 2009
Publisher: SPRINGER
Citation: 13TH INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING, VOLS 1-3,23,129-132
Abstract: Bone torsional deformity is excessive anatomical or axial twist of proximal portion with respect to distal. Accurate, simple, and quick measurement of torsional deformities at preoperative stage is clinically important for decision making in prosthesis design and surgery planning. Commonly used 2D methods for assessing excessive torsion use radiographic images or a set of slices of CT/MR images. The slices representing reference axes of distal and proximal portion are superimposed; the angle between the axes provides a measure of torsion. Representing 3D anatomical landmarks and reference axes in a 2D transverse slice or projected radiographic image leads to inaccurate and inconsistent values. Owing to the complex 3D shape of bones (ex. femur and tibia), there is a need for 3D model based assessment methods with little or no human intervention. Excessive torsion in the tibia and femur affects the procedure of total knee replacement. We present an automated methodology for assessing excessive torsional deformation of femur and tibia bone based on 3D anatomical landmarks based referencing. Reconstructed 3D bone model from a set of CT scan images using tissue segmentation and surface fitting is used in this methodology. Anatomical landmarks on femur and tibia bone are automatically identified based their shape and predefined landmarks spatial adjacency matrix. The identified 3D anatomical landmarks and computed functional and reference axes (femur: neck axis, condylar axis, and long axis; tibia: tibial plateau axis, long axis, and malleolus axis) are used for measuring torsional deformation, using 3D shape reasoning algorithms. The methodology has been implemented in a software program and tested on five sets of CT scan images of lower limb. The computerized methodology is found to be fast and efficient, with reproducible results.
URI: http://dspace.library.iitb.ac.in/xmlui/handle/10054/14805
http://hdl.handle.net/100/1595
ISBN: 978-3-540-92840-9
ISSN: 1680-0737
Appears in Collections:Proceedings papers

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