Emerging Techniques in Biomedical Imaging for Early Diagnosis of Chronic Diseases

Abstract

This paper reviews key developments in biomedical imaging, focusing on technologies such as magnetic resonance imaging (MRI), positron emission tomography (PET), optical coherence tomography (OCT), and AI-driven image processing methods. These innovations not only increase diagnostic accuracy but also allow for real-time, non-invasive assessments that are essential for personalized healthcare. The paper further explores the integration of AI and machine learning (ML) algorithms in imaging for disease prediction, as well as the growing role of multimodal imaging systems. The challenges associated with cost, accessibility, and standardization are discussed, along with potential solutions to foster widespread adoption in clinical practice. In conclusion, biomedical imaging techniques are key to transforming chronic disease diagnosis and management, offering unprecedented capabilities for early detection, monitoring, and treatment.