碩士 / 中原大學 / 生物醫學工程研究所 / 106 / According to the prediction of the Taiwan Alzheimer Disease Association, over 2% and 3% people will suffer to Alzheimer disease in 2017 and 2061 respectively. The earlier medical treatment of Alzheimer Disease (AD), the better for control AD and its disease progress. In clinical, it is too late after assess the level of AD by Clinical Dementia Rating (CDR). The method to get the ventricles and brain ratio in CT is a better choice. However, the assessment of brain atrophy ratio is not objective and time-consuming manually. An automatic system can provide the ventricles and brain ratio information for doctor is necessary.
In this project, we develop the computer aided detection (CAD) system by image processing methods to calculate the ventricles and brain ratio. According to the preliminary study, steps of this project including (1) To remove noise and separate the full area of brain through image preprocessing; (2) to detect the ventricles and brain by edge detection; (3) to calculate the volume of ventricles and brain; (4) to calculate the ratio of ventricles and brain; (5) to calculate the ratio of ventricles and brain and then to find the correlation with CDR. Finally, 80 sets of images were used which including 30 groups of images as the training group and 50 groups of images as the test group, for system effectiveness evaluation by supplemented with the patient''s CDR. After trained and verified, we expect our system could provide the useful data to aided diagnosis AD level for doctor.
Preliminary results and statistical analysis showed that the ventricles and brain ratio and CDR scores are proportional directly. The CT image diagnostic system except misjudgment and CDR score 3, demonstrates an accuracy of 88%, sensitivity of 81.82%, specificity of 92.86%, and kappa of 0.75. These indicate that the system for the diagnosis of Alzheimer''s disease is effective and accurate. In addition, the average segmentation split overlap rate for brain images in manual and developed system method is 93.14%, respectively. The system also provides ease of use interface for physician faster diagnosis.
The results in early diagnosis showed that the atrophy ratio of CT and MRI images and CDR scores are highly relatively. In the future, we can make use of CT imaging and MRI imaging as a primary diagnostic tool for early detection and reduce the patients’ need for other diagnostic procedures, thereby reducing medical waste.
| Identifer | oai:union.ndltd.org:TW/106CYCU5114022 |
| Date | January 2018 |
| Creators | Yu-Han Hsu, 許喻涵 |
| Contributors | Jenn-Lung Su, 蘇振隆 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 56 |
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