Analysis of Collagen Fiber Features in Medical Images

摘要

The medical images normally contain abundant medical information With image interpretations and feature analyses of medical images physiological processes or diseases can be further understood and this could be crucial for medical advances Regarding feature analyses four feature descriptions (including size shape color and texture) will be analyzed to clarify desired medical features These feature descriptions help people understand each medical feature clearly and then the image processing tool is applied to analyze every medical feature This thesis presents an algorithm of a computer-assisted method to dissect and quantify collagen fiber features of human skin including collagen fiber density orientation diversity and thickness in the medical image The Gabor filter is able to extract image texture and size information which used for quantifying collagen fiber orientation and thickness Moreover the Gabor filter and the Frangi filter are utilized for extracting shape information of collagen fiber according to the properties of collagen fiber and then the support vector machine method use shape information to obtain an accurate classification to segment collagen fiber region and further analyze collagen fiber density The proposed algorithm is able to overcome inconveniently using the instrument for feature analysis Comparing with other related works the proposed algorithm provides full analyses of collagen fiber features which has not only potential in biomedical image analyzing but also significant value to medical research

獎項日期	2015 2月 11
原文	English
監督員	Gwo-Giun Lee (Supervisor)