CELL IMAGE SEGMENTATION USING U-NET

Abstract

Medical image processing has been a field of large interest recently. Our field of interest in this work is Medical Image Segmentation. We perform Medical Image Segmentation to extract or visualise information regrating tissues cells or organs. In this work we are trying to extract cell body from the background. This segmentation is vital as it can help extract information about cells morphology which can later be used to train another neural network for prediction if a cell is healthy or non healthy. It can also be used to predict the type of cancer. We will use a FCN to perform the segmentation. From all FCN networks we chose U-Net to perform image segmentation. U-Net has proved to be very efficient for small datasets as our dataset. In this work we trained U-Net in different ways and changed its parameters to obtain the best model. We also designed two model evaluation functions for our field of interest. In the end we present our best model of U-Net to perform Cell Image Segmentation based on our experiment set.