Название: Biomedical Imaging: Advances in Artificial Intelligence and Machine Learning
Автор: Ankur Gogoi, Nirmal Mazumder
Издательство: Springer
Год: 2024
Страниц: 359
Язык: английский
Формат: pdf (true), epub
Размер: 61.0 MB

This book presents the rapidly developing field of Artificial Intelligence (AI) and Machine Learning and its application in biomedical imaging. As is known, starting from the diagnosis of fractures by using X-rays to understanding the complex structure and function of the brain, biomedical imaging has contributed immensely toward the development of precision diagnosis and treatment strategies for numerous diseases. While continuous evolution in imaging technologies have enabled the acquisition of images having resolution and contrast far better than ever, it significantly increased the volume of data associated with each image scan—making it increasingly difficult for experts to analyze and interpret. In this context, the application of Artificial Intelligence (AI) and Machine Learning (ML) tools has become one of the most exciting frontlines of contemporary research in biomedical imaging due to their capability to extract minute traces of various disease signatures from large and complicated datasets and providing clear insight into the potential abnormalities with excellent accuracy, sensitivity, and specificity. The book covers a range of topics, from the fundamentals of AI, ML, and Deep Learning (DL) to the latest applications of these techniques in the analysis and interpretation of various medical imaging modalities. The hallmark of this book will be the contributions from international leaders on different AI-aided advanced biomedical imaging modalities and techniques. Included will be comprehensive description of several of the technology-driven spectacular advances made over the past few years that have allowed early detection and delineation of abnormalities with sub-pixel image segmentation and classification. Starting from the fundamentals of biomedical image processing, the book presents a streamlined and focused coverage of the core principles, theoretical and experimental approaches, and state-of-the-art applications of most of the currently used biomedical imaging techniques powered by AI.

In the present day, Artificial Intelligence has been implemented to improve the healthcare sector. Many researchers have various opinions on the applications of Artificial Intelligence and Machine Learning (AI/ML) in healthcare. Artificial Intelligence (AI) in biomedical imaging is currently one of the most popular research topics in healthcare, and it’s generating a lot of interest with many scientific articles being published on this subject. While it offers numerous benefits, there are also accompanying challenges that require attention. The primary objective of this chapter is to emphasize the limitations in applying AI/ML in biomedical imaging. To understand the numerous challenges linked to the application of AI/ML in biomedical imaging. This will assist researchers in maintaining awareness of the challenges encountered when utilizing AI/ML in the context of biomedical imaging.








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