Biomedical imaging plays a central role in disease detection, monitoring, and treatment planning. With rapid technological advances, next-generation imaging systems are evolving beyond conventional modalities toward intelligent, multimodal, and personalized diagnostic platforms. Artificial intelligence (AI) enhances image acquisition, reconstruction, and interpretation, significantly improving accuracy and reducing diagnostic errors. Multimodal platforms, which integrate complementary imaging techniques such as MRI, PET, CT, and ultrasound, provide a more comprehensive understanding of disease states. Furthermore, the integration of personalized clinical diagnostics tailors imaging approaches to individual patients, enabling precision medicine. This paper explores the convergence of AI, multimodal imaging, and personalized healthcare in shaping the future of biomedical imaging. It highlights key technological breakthroughs, clinical applications, challenges, and ethical considerations, ultimately emphasizing how these innovations can transform healthcare delivery worldwide.