Natural User Interfaces in Medical Image Analysis

Although the capabilities of computer image analysis do not yet match those of the human visual system, recent developments have made great progress towards tackling the challenges posed by the perceptual analysis of images. This unique text/reference highlights a selection of important, practical applications of advanced image analysis methods for medical images. The book covers the complete methodology for processing, analysing and interpreting diagnostic results of sample computed tomography (CT) images. The text also presents significant problems related to new approaches and paradigms in image understanding and semantic image analysis. To further engage the reader, example source code is provided for the implemented algorithms in the described solutions. Topics and features: Describes the most important methods and algorithms used for image analysis, including holistic and syntactic methods Examines the fundamentals of cognitive computer image analysis for computer-aided diagnosis and semantic image description, introducing the cognitive resonance model Presents original approaches for the semantic analysis of CT perfusion and CT angiography images of the brain and carotid artery Discusses techniques for creating 3D visualisations of large datasets, and efficient and reliable algorithms for 3D rendering Reviews natural user interfaces in medical imaging systems, covering innovative Gesture Description Language technology Concludes with a summary of significant developments in advanced image recognition techniques and their practical applications, along with possible directions for future research This cutting-edge work is an invaluable practical resource for researchers and professionals interested in medical informatics, computer-aided diagnosis, computer graphics, and intelligent information systems.