Computational Analysis and Deep Learning for Medical Care

6Biomedical Image Segmentation by Deep Learning Methods

K. Anita Davamani^1*, C.R. Rene Robin², S. Amudha³ and L. Jani Anbarasi⁴

¹Anna University, Chennai, India

²Department of Computer Science and Engineering, Professor & Associate Dean, Jerusalem College of Engineering, Chennai, India

³Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai, India

⁴School of Computer Science and Engineering, VIT University, Chennai, India

Abstract

Deep learning methods have been employed to predict and analyse various application in medical imaging. Deep Learning technology is a computational algorithm that learns by itself to demonstrate a desired behaviours. Neural network processes the input neurons according to the corresponding types of networks based on algorithm provided and passes it to the hidden layer. Finally, it outputs the result through output layer. Deep learning algorithms tend to be more useful in different applications. It plays important role in biomedical image segmentations such as identifying skin cancer, lung cancer, brain tumour, skin psoriasis, etc. Deep learning includes algorithms like Convolutional Neural Network (CNN), Restricted Boltzmann Machine (RBM), Generative Adversarial Network (GAN), Recurrent Neural Network (RNN), U-Net, V-net, Fully Convolutional Attention Network (FCANET), Docker- powered based deep learning, ResNet18, ResNet50, SqueezeNet and DenseNet-121 which processes on medical images and helps ...