Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing

Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment. Image processing techniques began in the 1960s and have become more accurate, efficient, and self-learning in the 2020s. This book highlights the framework of robust and novel methods for medical image processing techniques in 2D and 3D and discusses real-time applications for artificial intelligence and machine learning.

Format: Paperback / softback
Length: 196 pages
Publication date: 25 September 2023
Publisher: Taylor & Francis Ltd

Digital images offer a multitude of advantages, including cost-effective and rapid processing, convenient storage and transmission, immediate quality evaluation, the ability to create multiple copies while maintaining high quality, swift and economical reproduction, and the flexibility for manipulation. In the realm of medicine, digital medical images assume a crucial role in our daily lives. Medical imaging refers to the creation of visual representations of the internal structures of the body for scientific and medical research, diagnosis, and treatment purposes, as well as providing insights into the functioning of internal tissues. This intricate process serves the dual purpose of identifying and managing disorders.

Medical imaging encompasses a wide range of techniques and procedures, including image acquisition, storage, presentation, and communication. These processes can be performed in both 2D and 3D dimensions, allowing for comprehensive analysis and interpretation of medical data. The versatility of 2D and 3D images enables them to be processed across various dimensions, depending on the specific requirements of a given problem. To effectively address these challenges, it is essential to identify and employ appropriate algorithms tailored to the characteristics of 2D or 3D images. These image processing techniques have a rich history, dating back to the 1960s, when they were initially applied in fields such as space exploration, clinical applications, the arts, and television image enhancement. However, significant advancements occurred in the 1970s with the development of computer systems, leading to significant reductions in the cost of image processing and accelerated processing speeds.

In the 2000s, image processing technology continued to evolve, becoming even more efficient, cost-effective, and user-friendly. The 2020s have witnessed further advancements, with image processing becoming more accurate, efficient, and self-learning. This book serves as a comprehensive resource that highlights the framework of robust and innovative methods for medical image processing techniques in both 2D and 3D. It explores existing and emerging challenges and opportunities within the medical field by employing various medical image processing techniques. The chapters delve into real-time applications of artificial intelligence and machine learning in medical image processing, discussing implementation strategies and techniques.

In conclusion, digital images have revolutionized the field of medicine by providing numerous benefits, including cost-effectiveness, rapid processing, convenient storage, immediate quality assessment, multiple copying, swift reproduction, and adaptable manipulation. Medical imaging plays a vital role in diagnosing and managing disorders, and the advancements in image processing technology have contributed to improved patient care and outcomes. This book serves as a valuable resource for researchers, practitioners, and students interested in the field of medical image processing, providing a comprehensive overview of existing and emerging techniques and their applications in the medical domain.

Weight: 453g
Dimension: 234 x 156 (mm)
ISBN-13: 9780367674953