Bone cancer detection using machine learning techniques

Bone cancer is one of the life threatening diseases which may cause death to many individuals. There must be an accurate detection and classification system available to diagnose bone cancer at early stage. Early detection of cancer seems to be the important factor in increasing the chance of cancer patient survival. Classification of cancer is one of the most challenging tasks in clinical finding and diagnosis. This work elaborates different machine learning techniques for tumor detection and classification. Machine Learning has a vast area of research, out of which medical image processing is significant area of work. In medical diagnosis like ulcer, fracture, tumor etc image processing made the work easier in finding the exact cause and best possible solution. In this work, bone Computed Tomography (CT) dataset in digital Imaging and communication in medicine (DICOM) format are used. Machine learning techniques applied on medical images for abnormality detection. It is observed that satisfactory level of improvement has been achieved by applying Machine Learning techniques. In this work different machine learning techniques for classification are elaborated.