A Color-Based Approach for Applying Automated Segmentation to Tumor Tissue Classification and Parameters Estimation
| Autor: | Shao-chien Chang, 章少謙 |
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| Rok vydání: | 2007 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 95 This paper presents a new color-based approach that applies automatic segmentation to tumor tissue classification on microscopy images. The color-based image analysis for tissue classification consists of three stages: (1) the color normalization aimed at reducing the quality variation of tissue image within samples of each individual subject or across subjects; (2) the automatic sampling from tissue image to eliminate the manually done time consuming sampling work; and (3) principal component analysis (PCA) to characterize color features with a given set of training data. Then our system classifies every pixel to a cluster that has the minimal Mahalanobis distance between the cluster center and the corresponding pixel than all the other ones. We evaluate the algorithm by comparing the performance of the proposed method with the semi-automated one. Experimental studies show good consistency between the auto and semi-automatic methods. Therefore, the proposed algorithm provides an effective tool for the evaluation of oral cancer images, and it can also be applied to other microscopic images with the same type of tissue staining. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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