Applications of Object Detection, Brain Tumor Detection and Classification
The highlight of the proposed work is to design an automated detection of the presence of tumor cells in the brain image and classification of normal and abnormal brain images.
Abstract
In the medical diagnosis system, detection and labelling of the specific region of interest and classification of diseases in Computer Tomography (CT) images and Magnetic Resonance Imaging (MRI) scans is a challenging task. Another major application is tumor or cancer type of cell detection as well as finding its size and location in the image. This research work focuses on addressing the most challenging research gaps existing in the field of medical diagnosis such as brain tumor identification in medical images, retrieving similar images or region from the database. In these applications, the major task involved in the extraction of sufficient and relevant features, is to identify the region of interest. With the extracted features development of efficient algorithms for the detection of region of interest (ROI) and the learning algorithms also required to classify the new images for the existing features. The highlight of the proposed work is to design an automated detection of the presence of tumor cells in the brain image and classification of normal and abnormal brain images.