Yanhui Guo – författare

Neutrosophic Set in Medical Image Analysis gives an understanding of the concepts of NS, along with knowledge on how to gather, interpret, analyze and handle medical images using NS methods. It presents the latest cutting-edge research that gives insight into neutrosophic set's novel techniques, strategies and challenges, showing how it can be used in biomedical diagnoses systems. The neutrosophic set (NS), which is a generalization of fuzzy set, offers the prospect of overcoming the restrictions of fuzzy-based approaches to medical image analysis.

Thermal Ablation Therapy: Theory and Simulation includes detailed theoretical and technical concepts of thermal ablation therapy in different body organs. Concepts of ablation technology based on different thermal ablation methods are introduced, along with changes in the tissues' mechanical properties due to thermal denaturation. The book emphasizes the mathematical and engineering concepts of RF and MW energy propagation through tissues and where high heating rates produced by MW systems can overcome the heat-sink effects from nearby vessels. The design and tuning of the MW antennas to deliver energy efficiently to specific organ systems such as the liver or lung is also covered.

Other sections cover the computational modeling of radiofrequency ablation and microwave ablation procedures for developing and implementing new efficient ablation in clinical systems, numerical simulations for different scenarios of different organs with different size using RF and MW ablation systems with different antennas'/probes design and configurations, and numerical techniques for temperature profile in tissues.

This book explores the challenges involved in handling medical big data in the diagnosis of neurological disorders. It discusses how to optimally reduce the number of neuropsychological tests during the classification of these disorders by using feature selection methods based on the diagnostic information of enrolled subjects. The book includes key definitions/models and covers their applications in different types of signal/image processing for neurological disorder data. An extensive discussion on the possibility of enhancing the abilities of AI systems using the different data analysis is included. The book recollects several applicable basic preliminaries of the different AI networks and models, while also highlighting basic processes in image processing for various neurological disorders. It also reports on several applications to image processing and explores numerous topics concerning the role of big data analysis in addressing signal and image processing in various real-world scenarios involving neurological disorders.

This cutting-edge book highlights the analysis of medical data, together with novel procedures and challenges for handling neurological signals and images. It will help engineers, researchers and software developers to understand the concepts and different models of AI and data analysis. To help readers gain a comprehensive grasp of the subject, it focuses on three key features:

● Presents outstanding concepts and models for using AI in clinical applications involving neurological disorders, with clear descriptions of image representation, feature extraction and selection.

● Highlights a range of techniques for evaluating the performance of proposed CAD systems for the diagnosis of neurological disorders.

● Examines various signal and image processing methods for efficient decision support systems. Soft computing, machine learning and optimization algorithms are also included to improve the CAD systems used.