A Study of Human Spine Segmentation and Disease Diagnosis Techniques for MRI Images

• Main Authors: Cheng-An Fang, 房宸安
• Other Authors: Hsien-Chu Wu
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/5ng3w3

碩士 === 國立臺中科技大學 === 資訊工程系碩士班 === 100 === This thesis focuses on medical imaging segmenting technology in the study of spinal diseases. Diseases of the spine can be divided into: disc degeneration, disc herniation, vertebral compression fractures and bone spurs. These diseases mainly occur in aged and middle-aged people. Because with the increase of age, the human spine is slowly aging, diseases of the spine will become public. Disc diseases can be scanned through some medical equipment; and medical imaging can be divided into two large categories CT and MRI images. In medical imaging, the usual practice is to make use of the MRI T2 images to judge the diseases of the spine. Since making the correct judgments depends heavily on professional doctors, this is not only time-consuming but also increases the workload of doctors. Therefore, the future trend is to use computer to do automatic diagnosis of spinal diseases, and automatic diagnosis is based on observing the area, shape varieties, and other features of the disease of the intervertebral disc. Thus, it is essential to extract the most significant feature to effectively segment and diagnose intervertebral disc. In Chapter 3, this thesis proposes an automatic method to segment the intervertebral disc and to diagnose the herniation of the intervertebral disc. This method contains the following major steps: segmenting the intervertebral disc, segmenting the nerve, and automatic diagnosis of the herniation of the intervertebral disc. The method of segmenting the intervertebral disc includes, first, removing the background and noises in the spine images, and then, analyzing the intervertebral disc. Here non- intervertebral disc objects are filtered by four intervertebral disc features, and finally the integral intervertebral disc objects will be kept. The method of segmenting the nerve includes, first, saving the brighter pixel value, and then removing the noises by morphology method. Finally, the nerve features will be kept in the image. The method of automatic diagnosis of the herniation of the intervertebral disc includes finding the overlapping objects between the intervertebral disc and the nerve image, and then labeling the objects of the intervertebral disc. This technology can effectively find out the abnormal parts of the intervertebral disc. Its average accuracy is as high as 99.88%.