Classification of Normal, Benign and Malignant Tissues using Fuzzy Texton and Support Vector Machine in Mammographic Images
| Autor: | Venkata RaghaDeepthiLoka, Sudhakar Putheti |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
business.industry
Computer science Quantization (signal processing) Feature vector Texton Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Content-based image retrieval medicine.disease Fuzzy logic Support vector machine Set (abstract data type) ComputingMethodologies_PATTERNRECOGNITION Breast cancer medicine Computer vision Artificial intelligence skin and connective tissue diseases business Quantization (image processing) |
| Zdroj: | International Journal of Computer Applications. 82:36-39 |
| ISSN: | 0975-8887 |
| DOI: | 10.5120/14243-2450 |
| Popis: | Content Based Image Retrieval systems are helpful to the radiologists in diagnosis of breast cancer. This paper presents a method for retrieving breast tissue as normal, benign or malignant in mammograms by using FuzzyTextons. In feature extraction first fuzzy texton images of mammograms are calculated. During the detection of fuzzy texton, fuzzy based quantization is performed to get more accurate textons. Then feature vectors are extracted for fuzzy textons and for efficient classification and retrieval Support Vector Machine is used. The proposed method was tested for a mammogram set from MIAS database. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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