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Explore emerging applications for AI, machine learning, and deep learning in biomedical imaging technologies
In Biomedical Imaging Technology: Signal Processing Strategies and Innovations, a team of distinguished researchers deliver an expert discussion on the application of imaging and signal processing techniques to healthcare technologies like X-ray, MRI, CT, ultrasound, and others. Beginning with an introduction to biomedical imaging, the book goes on to explain more advanced imaging technologies, like molecular and optical imaging.
This book provides a blend of theory and practical applications, exploring the role of AI and AI algorithms in enhancing diagnostic accuracy. It discusses machine and deep learning approaches for improving computer-aided diagnosis systems and the integration of signal processing within various imaging modalities.
Readers will also find:
A thorough introduction to contemporary approaches to optical imaging, including fluorescence imaging, photoacoustic imaging, and Optical Coherence Tomography (OCT)
Comprehensive explorations of image-guided interventions, theranostics in cancer treatment, and advancements in surgical navigation
Practical discussions of emerging trends in the field and up-and-coming innovations
Case studies and practical examples from real-world locations
Author Biography
Ayush Dogra, PhD, is an Assistant Director at Chitkara University, Punjab, India. His research areas include image fusion, image enhancement, image registration, and image denoising.
Shalli Rani, PhD, is a Professor and Director at Chitkara University, Punjab, India. She is a Senior Member of the IEEE and her research interests include Internet of Things, WSN, cloud computing, network security, and machine learning.
Ankita Sharma, PhD, is an Assistant Professor at Chitkara University, Punjab, India. She has authored numerous national and international publications in peer-reviewed journals.
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