Introduction
Advanced Imaging Applications for Interdisciplinary Engineering is a multidisciplinary exploration of the applications of A.I based imaging technologies and predictive modelling across nanotechnology, quantum imaging, and environmental science.
It covers AI-based image analysis and machine learning applications and innovations in nanoparticle-enhanced diagnostic imaging across modalities such as MRI, CT, and ultrasound. The book also explores quantum imaging techniques, including entanglement-based and ghost imaging, alongside applied computational models for tasks like air quality forecasting. Additional contributions include AI-driven traffic surveillance, image enhancement methods, and blockchain-based healthcare systems for secure data management.
The final sections address environmental studies, including waste analysis and groundwater contamination assessment. Overall, the volume bridges theory and real-world applications across healthcare, environmental monitoring, and intelligent systems.
Key Features
- - Multidisciplinary coverage spanning artificial intelligence, nanotechnology, quantum imaging, and environmental science.
- - Detailed insights into advanced imaging techniques, including CT, MRI, PET/SPECT, and quantum imaging methods.
- - Integrated perspectives on machine learning models for predictive analytics, image enhancement, and environmental forecasting.
- - Explores blockchain-based healthcare frameworks for secure and interoperable data management.
- - Combines theoretical foundations with practical case studies and real-world applications to provide experimental analysis across medical diagnostics, environmental monitoring, and infrastructure surveillance.
Target Readership:
Researchers, academics, students, and professionals seeking context on the application of AI and Data Sciences in medical diagnostics, environmental monitoring, and infrastructure surveillance.