Keywords : Euclidean Distance

Using Mask Technique and Center Detection for Congenital Dislocation of the Hip (CDH) Diagnosis

Nidal H. AL-Assady; Mafaz Mohsin Khalil Alanezi; Shahla H. Ahmad

AL-Rafidain Journal of Computer Sciences and Mathematics, 2007, Volume 4, Issue 1, Pages 107-122
DOI: 10.33899/csmj.2007.164000

The aim of this study, is the diagnosis of Congenital Dislocation of the Hip (CDH) from routine X-Ray Image by measuring the retardation of the growth center of the head of femur bone in the abnormal joint in comparison with the normal side in cases of unilateral CDH using  Mask Technique and algorithm of Center Detection and measurement. What is new about this study in comparison with the previous methods about diagnosis of CDH (which used artificial technique images matching subject to detect the diseased image only by compare the diseased images with normal image without giving any percent of disease) can be summarized by:
1.Going into the details of the X-Ray and cutting out the necessary parts ( head of femur ) for both the diseased and normal sides in cases of unilateral CDH, to make comparison between them instead of using the complete image.
2.Using Mask Technique and algorithm of Center Detection to extract the features (Center, Intensity value of the center, and Diameter ) from the two captured images. Then we do a comparison for both sides for these features using Euclidean Distance to know the diseased side from the normal one.
We applied this system in computer using Matlab 7.0 programming Langue.