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Future Directions and Innovations in AI and Imaging
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Author(s): Induni Nayodhara Weerarathna (Datta Meghe Institute of Higher Education and Research, India), Matteo Hirushan Jayakody Arachchige (University of Birmingham, UK), Austin Jojo Jallah (Datta Meghe Institute of Higher Education and Research, India), Mohammad Affan Kareem (Datta Meghe Institute of Higher Education and Research, India)and Kidus Manaye Mulugeta (Datta Meghe Institute of Higher Education and Research, India)
Copyright: 2026
Pages: 40
Source title:
Radiodiagnosis in the Era of AI
Source Author(s)/Editor(s): Praveen Kumar (Datta Meghe Institute of Higher Education and Research, Wardha, India), Prateek Verma (Dayananda Sagar University, Bangalore, India), Gaurav Vedprakash Mishra (Datta Meghe Institute of Higher Education and Research, Wardha, India), Gopal Singh Phartiyal (University of Leeds, UK)and Anurag Ashok Luharia (Datta Meghe Institute of Higher Education and Research, Wardha, India)
DOI: 10.4018/979-8-3373-0903-3.ch008
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Abstract
Radiology has been significantly impacted by artificial intelligence (AI), which has increased imaging capabilities, workflow efficiency, and diagnostic accuracy. With an emphasis on technologies like explainable AI, generative adversarial networks, and deep learning, this book chapter examines developments in AI applications in Imaging. These tools have changed medical Imaging by making automatic segmentation, picture reconstruction, and multimodal data integration possible. AI has also improved theranostic techniques, predictive analytics, and point-of-care diagnostics. Even though these developments mark a new age in radiography, issues including data privacy, moral dilemmas, and integration barriers still exist. This chapter highlights the revolutionary potential of AI-powered Imaging in both clinical and non-clinical applications while speculating about its future paths.
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