Application of Image Processing Technology to Develop Biochip Image Analysis System
| Autor: | Meng-Yao Lin, 林孟堯 |
|---|---|
| Rok vydání: | 2014 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 101 In the previous study, we have developed a biochip image analysis system, which use the 96 plate hole image. There will be distortions in the image, and result in poor system accuracy. Therefore, this study developed a biochip image analysis system that analyzes 4×4 and 6×6 hole plate biochip images. It can be remove the problem of image distortion and reduces manual interpretation image time in order to improve the efficiency of the chip analysis. The biochip image was entered through this system and processed through the image pre-processing, image segmentation, and feature classification, three steps. First of all, in the image pre-processing step, median filter and histogram equalization are used to remove noise and smoothing the image and to enhance the image contrast. Secondly, the binarization method is used to separate the background and the reaction point for image segmentation. Then, using the circle equation to remove the noise outside of plate hole, and split the reaction point. Finally, the image is classifyed into clear feature point and blurs feature point. The bi-leveled image of clear feature point directly compared with the characteristics of the sample and analyzed the results. The image of blur feature point compared with the characteristics of the sample and analyzed the results by gray value of the original image. Designed pantom image is used to test and biochip images which including, 191 Food chip image (4×4 microarray), 190 HPV chip image (6×6 microarray) and 152 NTM chip image (6×6 microarray) are used to evaluate this system. The results shows that the order of the reaction point observations indicate the accuracy rate of food bacteria image, HPV clinical specimen image, and NTM clinical specimen image reached 99.57%, 99.50%, and 99.75%. In terms of the accuracy of a single hole plate, the average of the system's accuracy was 92.68%. After the removal of invalid responses, positive and negative results of the accuracy rates for three kinds of biochip image were 95.24%, 96.81%, and 98.51%, respectively. In conclusion, the system removed the distortion of 96 holes plate image by using single hole plate image, and carry on the feature classification for image. It can improve the accuracy of biochip image analysis system and the efficiency of the image interpretation which lead a positive assistance for biochip users and industry. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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