A non-invasive methodology for the grade identification of astrocytoma using image processing and artificial intelligence techniques
To suggest a non-invasive method for classification of Astrocytoma through rigorous training and testing. To compare and conclude the best medical image segmentation technique. To develop an efficient automatic feature selection technique for grade identification. To analyze and quantify the performance of classifiers constructed for the grade identification of Astrocytoma (tumor).
astrocytoma image segmentation feature selection tumor isolation feature extraction grade classification