Full Description
This book offers an approachable guide to the use of artificial intelligence in neuroradiology. Artificial intelligence is evolving rapidly and has begun to have an impact on how neuroradiology is conducted. Thus, being familiar with artificial intelligence and its utility is essential for the modern neuroradiologist.
This text includes an overview of artificial intelligence in neuroradiology, including how it's conducted and how it's applied in clinical practice. In particular, machine learning and deep learning algorithms are reviewed as pertains to neuroimaging applications, such as optimizing workflow, quality assurance, including noise reduction and reduction in scan time, image segmentation and volumetric measurements, diagnosis, and treatment response prediction. This is based on the current research literature with a consideration for future directions. Finally, ethical and legal issues related to AI for medical imaging are discussed, as well as regulatory and HIPAA compliance issues. Illustrative examples are included throughout.
This is an ideal guide for neuroradiologists and neurologists.
Contents
Overview of machine learning and deep learning algorithms.- How to do AI research for neuroimaging.- Logistical considerations related to incorporating AI into the radiology workflow, regulatory constraints, and HIPAA compliance issues.- AI for workflow optimization.- AI for quality assurance and imaging quality improvement.- AI for anatomy and lesion segmentation.- AI and radiomics for tumor characterization and prognosis.- AI for evaluating neurodegenerative disease.- AI for cerebrovascular disease.- Ethical and legal issues related to AI for medical imaging and other resources.
