Medical Image Analysis Using Convolutional Neural Networks

Abstract

Medical data can be expressed in many different ways such as texts, electronic health records, images and videos. The tool utilized plays an important role for the quality of the data. With time changing and some situations changing, data has different attributes. These are affected by other factors too, which cannot be considered. A very important element of medical data is medical imaging. Medical image examination is an important quality that assists medical practitioners in making sound decisions in modern healthcare systems. Diagnosis of many diseases, such as diabetic retinopathy detection, brain tumor, lung cancer etc., relies greatly on medical image analysis. Various medical image analysis includes: image classification, image segmentation and detection, image denoising, etc. This study addresses the challenges in medical image classification. To enhance the quality of an image that offers appropriate images or information, image processing is a method that converts an ordinary image to a digital form.