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

by: Snehan Biswas (Author),Amartya Mukherjee(Author),Nilanjan Dey(Author)&0more

Publisher: CRC Press

Edition: 1st

Publication Date: 2024/12/2

Language: English

Print Length: 184 pages

ISBN-10: 1032589272

ISBN-13: 9781032589275

Book Description

This book serves as a source of introductory material and reference for medical application development and related technologies by providing the detailed implementation of cutting-edge deep leaing methodologies. It targets cloud-based advanced medical application developments using open-source Python-based deep leaing libraries. It includes code snippets and sophisticated convolutional neural networks 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.Focuses on solving real-world medical imaging problems.Discusses advanced concepts of deep leaing along with the latest technology such as GPT, stable diffusion, and ViT.Develops applicable knowledge of deep leaing using Python programming, followed by 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 leaing.

About the Author

This book serves as a source of introductory material and reference for medical application development and related technologies by providing the detailed implementation of cutting-edge deep leaing methodologies. It targets cloud-based advanced medical application developments using open-source Python-based deep leaing libraries. It includes code snippets and sophisticated convolutional neural networks 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.Focuses on solving real-world medical imaging problems.Discusses advanced concepts of deep leaing along with the latest technology such as GPT, stable diffusion, and ViT.Develops applicable knowledge of deep leaing using Python programming, followed by 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 leaing.