The goal of this thesis is to get acquainted with methods of determining bone mineral density from appropriate tissue types in diagnostic CT data and possibly modifying or extending them in order to make the bone quality diagnosis more reliable. The thesis begins by introducing the issue of determining bone quality. Next, a method that takes cortical bone deformations into account as well as bone mineral density is introduced. Accuracy assessment based on opinion of a medical expert suggests positive outcome of future objective accuracy assessment utilizing so far unavailable base of calibrated CT data, that is needed before deployment into clinical practice. If the accuracy of the suggested method is confirmed this way, this work provides a so far absent tool for fully automatic preventive diagnostics of osteoporosis.

This thesis deals with the segmentation and classification of paraspinal muscle and subcutaneous adipose tissue in 3D CT image data in order to use them subsequently as internal calibration phantoms to measure bone mineral density of a vertebrae. Chosen methods were tested and afterwards evaluated in terms of correctness of the classification and total functionality for subsequent BMD value calculation. Algorithms were tested in programming environment Matlab® on created patient database which contains lumbar spines of twelve patients. Following sections of this thesis contain theoretical research of the issue of measuring bone mineral density, segmentation and classification methods and description of practical part of this work.

No description available.