A Beginner's Guide to Medical Application Development with Deep Convolutional Neural Networks

This book serves as source of introductory material and reference for medical application development and related technologies by providing the detailed implementation of the cutting-edge deep learning methodologies. It targets the cloud based advanced medical application developments using open-source python based deep learning libraries. It includes code snippets and sophisticated Convolutional Neural Networks (CNNs) to tackle real-world problems in medical image analysis and beyond. Features: Provides programming guidance for creation of sophisticated and reliable neural networks for image processing. Incorporates the comparative study on GAN, Stable diffusion and its application on Medical Image data augmentation. Focusses on solving real world medical imaging problems. Discuses advanced concepts of Deep Learning along with latest technology like GPT, Stable Diffusion, ViT. Develops applicable knowledge of Deep Learning using Python programming, followed with code snippets and OOP concepts. This book is aimed at graduate students and researchers in medical data analytics, medical image analysis, signal processing, and deep learning.