Thermal Imaging and Computational Intelligence Techniques in Disease Detection

The text presents a compilation of research and methodologies at the intersection of thermal imaging, medical diagnostics, and artificial intelligence for non-invasive early disease detection, diagnosis, and monitoring across a spectrum of medical conditions. The text presents a compilation of research and methodologies at the intersection of thermal imaging, medical diagnostics, and artificial intelligence for noninvasive early disease detection, diagnosis, and monitoring across a spectrum of medical conditions. It highlights the importance of using the latest technologies to improve performance, productivity, efficiency, and security in healthcare without sacrificing reliability or accessibility. The structured chapters provide both foundational and advanced insights into the use of infrared thermography in breast thermogram analysis, osteoporosis detection, cancer research, diabetic neuropathy, oral cancer, and skin lesions, emphasizing how computational intelligence augments diagnostic precision. This book: Covers the application of thermograms in the early detection of various diseases using faster and more efficient image processing and intelligent classification algorithms. Discusses the use of different image processing methods in thermal imaging applications to diagnose various medical issues. Focuses on implementing the latest artificial intelligence techniques including machine learning to automate the decisions based on thermograms to aid medical experts in quick and effective diagnosis with early detection of diseases. Presents an in-depth analysis of the application of infrared thermal imaging in the diagnosis of specific diseases like cancer, osteoporosis, skin lesions, and diabetic neuropathy focusing on the computational techniques. It is primarily written for senior undergraduates, graduate students, and academic researchers in medicine, bioengineering, electrical engineering, electronics and communications engineering, computer science engineering, and biomedical engineering.