Anatomical structures are extracted from medical pictures using the image segmentation application known as medical image segmentation. To anticipate the abnormalities of the bone, medical picture segmentation and classification are performed in this procedure. More precisely, we provide a technique to enhance categorization in order to increase process performance. On the basis of convolutional neural networks, a framework for feature categorization is suggested. As a result, the performance was assessed using the criteria of accuracy, sensitivity, and specificity. The major goal of this procedure is to determine if the bone X-ray picture is aberrant and to indicate whether the input is normal or abnormal. One of the goals is to increase the process's performance.Precision will be poor when the Region is segmented manually, but it will be high in this procedure since detection and segmentation are based on an automatic method. The primary goal of this procedure is to automatically and accurately diagnose bone abnormalities.

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