Convolutional Neural Network for Automated Analyzing of Medical Images

Abstract

Convolutional Neural Network CNN) is one of the deep learning algorithms. It is useful for finding patterns in images. Intelligent software automates understanding images and speech. Extracting distinct features, by their own induces intelligent to software for identifying objects, recognizing faces and diagnosing diseases from medical images. With the help of CNN, software on their own acquires the knowledge of patterns from raw data. These developments play a prominent role in medical imaging. Classification, Segmentation and diagnosing are the area where CNN marked its importance. About CNN there has been a large array of improvements achieved in the last few years. We provide a short overview of the role of CNN in medical image analysis. A shallow CNN model is proposed as an automatic diagnosing system. This work specifically concentrates on three key elements: (1) building blocks of convolutional neural networks (2) introduction of various CNN architecture; (3) Challenges in implementing CNN for analyzing medical images.