Brain Images Analysis: Application of Artificial Intelligence - by Ricky Collier (Hardcover)

About the Book

Brain image analysis refers to the process of studying and interpreting images of the brain obtained tthrough various imaging techniques. It involves the use of advanced imaging techniques to study the structure, function, and connectivity of the human brain. Techniques such as MRI (Magnetic Resonance Imaging), fMRI (functional MRI), PET (Positron Emission Tomography), and CT (Computed Tomography) scans provide detailed insights into brain anatomy, neural activity, and metabolism. These images are analyzed using computational methods and algorithms to extract meaningful data, such as identifying brain regions, mapping neural pathways, and correlating brain activity with cognitive functions or diseases. This analysis is crucial for diagnosing neurological conditions, monitoring effects and advancing research in brain science. Artificial Intelligence (AI), particularly machine learning and deep learning techniques, has revolutionized brain image analysis. AI algorithms can process large volumes of brain imaging data quickly and accurately, enabling early detection and diagnosis of neurological disorders like Alzheimer's disease, brain tumors, and multiple sclerosis. This book strives to provide a fair idea about brain image analysis and helps develop a better understanding of the latest advances within this field. While understanding the long-term perspectives of the topics, the book makes an effort in highlighting their impact as a modern tool for the growth of the discipline. This book aims to equip students and experts with the advanced topics and upcoming concepts in this area.

Book Synopsis

Brain image analysis refers to the process of studying and interpreting images of the brain obtained tthrough various imaging techniques. It involves the use of advanced imaging techniques to study the structure, function, and connectivity of the human brain. Techniques such as MRI (Magnetic Resonance Imaging), fMRI (functional MRI), PET (Positron Emission Tomography), and CT (Computed Tomography) scans provide detailed insights into brain anatomy, neural activity, and metabolism. These images are analyzed using computational methods and algorithms to extract meaningful data, such as identifying brain regions, mapping neural pathways, and correlating brain activity with cognitive functions or diseases. This analysis is crucial for diagnosing neurological conditions, monitoring effects and advancing research in brain science. Artificial Intelligence (AI), particularly machine learning and deep learning techniques, has revolutionized brain image analysis. AI algorithms can process large volumes of brain imaging data quickly and accurately, enabling early detection and diagnosis of neurological disorders like Alzheimer's disease, brain tumors, and multiple sclerosis. This book strives to provide a fair idea about brain image analysis and helps develop a better understanding of the latest advances within this field. While understanding the long-term perspectives of the topics, the book makes an effort in highlighting their impact as a modern tool for the growth of the discipline. This book aims to equip students and experts with the advanced topics and upcoming concepts in this area.