A Review on Medical Image Analysis Using Deep Learning
Raju Egala, M. V. S. Sairam
Abstract
The objective of the medical image analysis is to increase the effectiveness of the diagnosis options. The Coevolution Neural Network (CNN) is the predominant neural network architecture used in Deep Learning (DL) for medical image analysis. Recently, various innovative technics of DL such as different activation functions, optimization technics, and loss functions have enhanced the performance of CNNs. The Deep Learning CNN (DL-CNN) assists as valuable tool to assist radiologist in diagnosis and improves efficiency and accuracy. Numerous DL-CNN methods have been published to analyze medical images. This paper compiles the performance metrics of DL-CNN, as presented by various authors. This paper reviews the image analysis of six different diseases, viz., lung cancer, colorectal cancer, liver cancer, stomach cancer, breast cancer, and brain tumors.