MRI Brain Image Retrieval Using Multi Support Vector Machine Classifier
Abstract— Content of image retrieval is the process of finding relevant image from large collection of image database using visual queries. Medical images have led to growth in large image collection.To enhance the medical image retrieval for diagnostics,research and teaching purposes is done by CBIR. The content of medical images is difficult to describe in words or textual form. The proposed system uses multiple image queries for finding desired images from the database.< Final Year Projects > The system performance is improved by the multiple image queries instead of single image query. Pre-processing of the query image is done by median filter to remove the noise. Then the filtered image is given as input to the feature extraction technique which is a transformation of input image into set of features such as texture and shape. Feature extraction is done by the Gray level co-occurrence matrix algorithm that contains information about the position of pixels having similar gray level values.The feature optimization is done on the extracted features to select best features out of it to train the classifier. SVM (Support Vector machine) classifier is to group items that have similar feature values into three categories such as normal, benign and malignant.
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