Automatic Image Analysis for Detection and Evaluation of Pelvis Disease

• Main Authors: Chien-Chi Chen, 陳建祺
• Other Authors: Yung-Nien Sun
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/93197914468074903446

碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 95 === The goal of this thesis is to construct a system which analyzes the AP view X-ray images for hip and hip joint, and the system can also evaluate the extent of hip dislocation. The developed model of the proposed system is based on the doctor’s professional knowledge and provides objective parameters for clinical applications. We hope the proposed system can help doctor in decreasing the diagnostic time while improving the outcomes of therapy or surgery. According to the sex, age, and body type, there exist many differences in hip images. Therefore, using a fixed model to fit every image does not work well. As the hips usually have similar shapes, an adaptive model which satisfies the general shape of hip may result in a better result. Active Shape Model (ASM) which can transform to accommodate the variable image information is such an elastic method. We adopt this method as the initial shape in segmenting the hip images. The femur、ilium and obturator foramen belong to independent anatomical structures. This thesis segments the above structures using the following procedures: (1) Using active shape model to construct three models from the training pattern. (2) Refine the bone contour by using the nearby gray levels of landmarks. (3) Estimating the Simon’s line and Shenton’s line, respectively. (4) Based on the extracted contour from X-ray image, we can get the landmarks and calculate the least square error distance from the landmark to Simon’s line, or to the Shenton’s line. (5) Automatically calculating the error distance as the basis in diagnosing the dislocation of hip structure.