Transfer Learning based Hybrid Image Clustering for Brain MRI Images

Detection of brain cancer is a tedious and very crucial job. Usage of image based clustering can provide a efficient and unsupervised method of brain cancer detection. Due to the nature of image data, direct clustering is highly impossible and inefficient. To overcome the above limitation, hybrid learning methods are adopted. Efficient utilization of transfer learning can improve the accuracy and save time for image based clustering. In the following work, we have proposed a hybrid clustering model based on transfer learning to achieve brain tumor detection.