الفهرس 
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Abstract
The human knee joint has been the subject of investigation from many points of view
as it is an important component of the human motion system. Computer Tomography(CT)
images are usually evaluated by human evaluator in the medical praxis, however, this can be
extremely difficult due to the similar gray scale representation of the synovial fluid between
the opposite cartilage surfaces of femur, tibia and the cartilage covering surfaces. Efficient
and sensitive computer methods for contour detection and segmentation can improve the
quality of evaluation. Accurate computation of distances and directions within the joint
provides solid basis for orthopedic handling and surgery. Many important properties of the
knee joint can only be evaluated in three dimensions. The bone and cartilage surfaces have
complicated shapes in 3D and the motion takes place in 3D. Consequently, 3D computer
programs built models using information extracted from the 2D images.
The purpose of this thesis is to offer a convenient geometrical modeling in a visual
system to investigate the human knee joint by computer tools. The proposed model consists of
the following system: input data, storing & handling of CT images of the knee, methods &
programs for image analysis, 3D surface reconstruction, graphical & geometrical tools for the
detailed analysis of the shape and the contact path motion of the knee. Most important
elements of the system are reported in this thesis. New algorithms and computer programs are
represented herein to predict the point clouds by slice adaptive threshold from CT images.
These algorithms handle imperfections coming from contour detection and measurements.
Then a continuous surface fit starts with topological ordering of points, which is done by
creating a mesh grid from point clouds. Mesh grid provides neighborhood relations, which is
important for fitting surfaces and for geometric calculations. Also a 3D model for the
reconstruction of human knee joint represented by Bezier surface and polynomial regression
is achieved and discussed. Finally a computer aided geometric model is used to develop and
predict the cartilage and menisci of the knee. An accurate description of the total knee
replacement is achieved.