Author(s) :

Banothu Anitha, Mr. B. Ravindar Reddy.

Volume/Issue :

Abstract :

Bone sarcoma, usually known as bone cancer, is a rare type of cancer that refers to an abnormal growth of tissue inside the bone, with high probability to spread to other parts of the body. It commonly affects children, teenagers and young adults. As for all other types of cancer (breast, lung, prostate, stomach, brain...), there are no identified causes for bone cancer. Therefore, only an early detection could help increasing the chances to survive a bone sarcoma. The association of medical imaging modalities (such as X-ray, MRI and CT imaging) with image processing techniques can provide more accuracy while detection eventual bone tumors. In this paper, we introduced a new method for sarcoma diagnosis, using a Generalized Gaussian Density analysis (GGD) For future extraction and convolutional neural network (CNN) classification model. The process starts by generating sub-images of a given size from the processed bone MRI and conducting a GGD analysis on each of the sub-images. Then, a region of interest (ROI) corresponding to the sub-images with the highest value of the shape parameter α is selected from the original MRI. The classification performance by CNN model and gets good results in terms of accuracy, precision, recall, and F1-score.

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