Brain Tumor Segmentation using Deep Learning in Medical Image Processing: A review

Sunil Kumar Agrawal, Dr. Ashutosh Mishra

Brain tumor, CNN, Deep Learning, image segmentation, MRI.

In the medical image processing area, brain tumor segmentation is a very crucial task. Early identification of brain tumors enhances treatment options and increases the likelihood that the patient will survive. Tumor segmentation from MRI images for diagnosis purposes is a difficult and time is taken process. Image segmentation of brain tumors must be done automatically. This study aims to represent an overview of MRI-based tumor segmentation techniques. Deep learning approaches for automatic segmentation have rapidly acquired popularity since they produce cutting-edge results and are better suited to this task than previous methods. Deep learning methods can also be used to efficiently process and objectively evaluate vast amounts of MRI-based image data; however, in this study, we have focused on deep learning approaches which are used in the medical field. First, a brief overview of brain tumors and strategies for segmenting them is provided. Lastly, we have concluded that the deep learning approach is the most promising technique for tumor segmentation.