Revolutionising Medical Imaging with Computer Vision and Artificial Intelligence (Original Publisher)
$35.00
Transform your understanding of modern radiology with Revolutionising Medical Imaging with Computer Vision and Artificial Intelligence (2024)—a cutting-edge guide that explores how AI and computer vision are reshaping diagnostic workflows, image analysis, and clinical decision-making across the healthcare spectrum.
Description
The 1st Edition of Revolutionising Medical Imaging with Computer Vision and Artificial Intelligence offers an in-depth and forward-thinking exploration into how emerging technologies are redefining diagnostic accuracy, speed, and accessibility. Tailored for radiologists, data scientists, healthcare professionals, and medical imaging researchers, this book bridges the gap between advanced computer vision algorithms and their real-world application in radiology, pathology, and clinical diagnostics.
From AI-driven segmentation tools to deep learning models that detect subtle abnormalities in scans, this comprehensive resource brings together current research, implementation strategies, ethical considerations, and future outlooks. It is ideal for anyone looking to stay ahead in the rapidly evolving field of medical imaging innovation.
Key Features & Highlights
- Comprehensive AI Frameworks – Learn how artificial intelligence is integrated into imaging workflows, from preprocessing to diagnosis.
- Real-World Case Studies – Analyze clinical examples where AI and computer vision have significantly improved patient outcomes.
- Cutting-Edge Research Insights – Stay current with the latest breakthroughs in machine learning, neural networks, and image interpretation.
- Ethical & Regulatory Discussions – Understand the legal, ethical, and privacy implications of using AI in healthcare environments.
- Multidisciplinary Approach – A valuable reference for radiologists, clinicians, biomedical engineers, AI developers, and researchers.
Topics Covered
This edition includes core chapters on:
- Fundamentals of computer vision and AI in healthcare
- AI models for medical image segmentation and classification
- Deep learning in radiography, CT, and MRI
- Automated disease detection and clinical decision support
- Explainable AI (XAI) and model interpretability
- Data quality, labeling, and training datasets in medical imaging
- Ethics, bias, and regulatory standards in AI-driven diagnostics
About the Author
The author is a recognized thought leader in medical AI and diagnostic imaging innovation, with expertise spanning radiology, machine learning, and healthcare data science. Their multidisciplinary experience brings both technical depth and clinical relevance to every chapter.
Technical Specifications
- File Format: PDF
- File Size: Approx. 55 MB
- Language: English
- Year of Publication: 2024
- Edition: 1st
- Compatible Devices: PC, Mac, Kindle, iOS, Android, and major eReaders
Frequently Asked Questions
Q1: Is this book suitable for non-technical readers or clinicians with minimal programming background?
A: Yes. While the book includes technical content, it presents complex AI concepts in an accessible way for healthcare professionals and medical students without deep coding experience.
Q2: Does the book include practical implementation examples or is it purely theoretical?
A: It includes both—real-world use cases, model applications, and conceptual explanations to provide a well-rounded, practice-ready understanding.
Additional information
| Publisher |
Other Publisher |
|---|---|
| Published Year |
2024 |
| Language |
English |
| ISBN |
978-1036410612 |
| File Size |
4.6 MB |
| Edition |
1 |
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