Brain Tumor Detection Using Deep Learning

Abstract

Brain tumors are developed as a result of unregulated and fast cell proliferation. It may result in death if not treated in the early stages. The imaging technology used to diagnose brain tumors is known as magnetic resonance imaging (MRI). Early detection of brain tumors is critical in medical practise in order to determine whether the tumor will progress to malignancy. For picture categorization, deep learning is a useful and effective method. Deep learning has been widely used in a variety of sectors, including medical imaging, because its application does not necessitate the expertise of a subject matter expert, but does necessitate a large amount of data and a variety of data in order to produce accurate classification results. The deep learning technique for image categorization is the convolutional neural network (CNN).In this research work , two different models are used to categorize brain tumors and their results were evaluated using performance metrics like accuracy and precision and the results were impressive

Detection of Brain Tumour based on Optimal Convolution Neural Network

“…It is important to make a compromise between the performance of the model and the size of the image input [21]. Typically, the input images are reduced to a fixed size that is computationally efficient for the deep learning model and large enough to retain important information [22] Learning the depth system used and the nature of the medical image being analysed can affect the sample size for the scaling of the input image [23].…”