MRI Classification and Segmentation of Cervical Cancer to Find the Area of Tumor
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 7
Abstract
Automated classification and detection of tumors in different medical images is motivated by the necessity of high accuracy when dealing with a human life. The detection of the Cervical Tumor is a challenging problem, due to the structure of the Tumor cells. This proposed system presents a segmentation method spatial fuzzy clustering algorithm, for segmenting Magnetic Resonance images to detect the Cervical Tumor in its early stages and to analyze anatomical structures. The vector machine will be used to classify the whether test image of Cervical MRI is normal or abnormal. Here Dual Tree CWT multi scale decomposition is used to analysis texture of an image. The segmentation results will be used for early detection of Cervical Tumor which will improve the chances of survival for the patient. To implement an automated Cervical Tumor classification decision making was performed in two stages: feature extraction using GLCM and the classification using SVM. The performance of this classifier was evaluated in terms of training performance and classification accuracies. The simulated results will be shown that classifier and segmentation algorithm provides better accuracy than previous method.
Authors and Affiliations
S. S. Dhumal, S. S. Agrawal
Keywords
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