Computer-Aided Classification of Hepatocellular Carcinoma and Liver Abscess Based on Optimized Texture Feature Sets in Ultrasound Images
| Autor: | Pham Quoc Phu |
|---|---|
| Rok vydání: | 2015 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 103 Most of clinical technologies of detecting dangerous liver diseases are dependent on liver biopsy sampling. With the advances of medical technology in recent years, non-invasive detecting methods (e.g., based on ultrasound images) have been widely applied to diseases diagnosis. Therefore, the liver disease diagnosis becomes easier and more comfortable than before. This could reduce the risk of pain, infection or other injuries from biopsy tests. Nevertheless, for the less experienced clinicians, it could not be easy to clearly identify liver diseases from ultrasound images just by their eyes. In order to overcome this problem, we applied the technologies of image processing and pattern recognition to the computer-aided classification system designed for ultrasound images between hepatocellular carcinoma (hcc-the most common type of liver cancer) and liver abscess. In this study, the feature extraction methods (Gray-Level Co-Occurrence Matrix and Gray-Level Run-Length Matrix) were used to analyze the ultrasound images. Then the feature selections (Sequential Forward Selection, Sequential Backward Selection or F-score) eliminated the redundant features to obtain the optimal feature set before classifiers (Support Vector Machine or Neural Network) discriminated the different kind of diseases. This study can provide the diagnosis help for an inexperienced clinician. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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