Brain Tumor Diagnosis Based on Lasso Classifier
|International Journal of Engineering Trends and Technology (IJETT)|
|© 2014 by IJETT Journal|
|Year of Publication : 2014|
|Authors : K.Lakshmi Narayana , M.Mariya Dasu
K.Lakshmi Narayana , M.Mariya Dasu. "Brain Tumor Diagnosis Based on Lasso Classifier", International Journal of Engineering Trends and Technology (IJETT), V15(8),374-378 Sep 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Computed tomography images are widely used in the diagnosis of brain tumour because of its faster processing, avoiding malfunctions and suitability with physician and radiologist. This study proposes a new approach to automated detection of brain tumour. This proposed work consists of various stages in their diagnosis processing such as reprocessing, anisotropic diffusion, feature extraction and classification. The local binary patterns and gray level co-occurrence features, gray level and wavelet features are extracted and these features are trained and classified using LASSO classifier. The achieved results and quantitatively evaluated and compared with various ground truth images. The proposed method gives fast and better segmentation and classification accuracy. We use free-response receiver operating characteristic curves to evaluate detection performance, and compare the proposed algorithm with several existing methods. In our experiments, the proposed framework outperformed all the other methods tested.
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Brain Tumour, Lasso Classifier, Segmentation, image.