The Application Of Artificial Intelligence In Interventional Neuroradiology

The application of artificial intelligence in interventional neuroradiology

Artificial Intelligence in Medical Imaging in China

This book overviews the latest development of Artificial Intelligence in medical imaging in China. Consisted of thirteen chapters, this book discusses development, status, achievements, prospects, visions, bottlenecks, and future challenges affecting development of artificial intelligence in medical imaging from different aspects of government supervision, industrialization, education, academic research and application implementation. It will facilitate better communication between China and foreign countries in all directions of medical imaging AI for all stakeholders.

AI in Diagnostic Radiology: Clinical Applications and Case-Based Insights

AI rapidly transforms diagnostic radiology, offering powerful tools to enhance image interpretation, streamline workflows, and improve diagnostic accuracy. By utilizing deep learning algorithms trained on medical images, AI systems can detect abnormalities with precision comparable to experienced radiologists in certain contexts. These advancements have found real-world application in areas like chest X-ray analysis, mammography, CT and MRI interpretation, and triage in emergency imaging. Case-based insights demonstrate how AI assists in early disease detection, supports differential diagnosis, and reduces diagnostic errors, contributing to better patient outcomes. However, effective clinical integration requires careful validation, consideration of ethical implications, and collaboration between radiologists and AI developers to ensure technology works with, rather than replaces, human expertise. AI in Diagnostic Radiology: Clinical Applications and Case-Based Insights explores the use of AI in diagnostic radiology to enhance image analysis, improve diagnostic accuracy, and streamline clinical workflows. It explains real-world applications through case-based insights, demonstrating how AI supports radiologists in detecting and interpreting medical conditions. This book covers topics such as medical detection, deep learning, and radiology, and is a useful resource for medical professionals, computer engineers, academicians, researchers, and scientists.