"Medical Image Processing Using AI" provides a thorough review of the current breakthroughs, methodologies, and applications in medical imaging with artificial intelligence (AI). This book by leading medical imaging and AI researchers delves into the junction of these two fields, giving readers the insights and practical expertise to navigate AI-driven medical image analysis. The book covers medical imaging and AI's fundamental principles and methods, including image acquisition, preprocessing, feature extraction, and machine learning algorithms for medical image processing. Readers master the key principles and strategies needed to use AI in medical imaging via simple explanations and examples. As readers progress through the chapters, they are introduced to a diverse array of clinical applications and use cases where AI has made significant inroads, revolutionizing diagnostic workflows, treatment planning, and patient care across various medical specialties. Real-world case studies and examples illustrate how AI algorithms are being deployed in radiology, pathology, oncology, cardiology, and other fields to enhance diagnostic accuracy, improve treatment outcomes, and optimize clinical decision-making. Moreover, the book explores the ethical considerations, challenges, and future directions shaping the landscape of AI-driven medical image processing. From data privacy and algorithmic bias to regulatory frameworks and clinical integration, readers gain insight into the broader implications of AI in healthcare and the importance of responsible and equitable deployment of AI technologies.
