Enhanced Computer-Aided Detection of Bone Fractures and Classification based on GRUSVM Approach

Abstract

There has been a lot of recent technology advancement in the medical profession. However, in this regard, several time-tested conventional approaches remain popular and effective. X-rays are one technique used to detect bone fractures. A crack doesn't have to be very large for it to go undetected, though. Consequently, they require systems that are both ingenious and well-implemented. The efficiency of the training model, edge detection, segmentation, feature extraction, and preprocessing are all utilized in the suggested method. noise cancellation methods are employed during the preliminary processing of the photos. Edge detection is a method used to identify the boundaries between two things. In order to get more out of an image, segmentation is used. Sharpening an image is part of the feature extraction process that enhances the difference between light and dark areas. Performance is measured using the GRU-SVM Model. The proposed technique is evaluated in comparison to the GRU and SVM models. When compared to older techniques, this one is a huge improvement.

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