Artificial Intelligence in Medical Imaging: Applications of Deep Learning for Disease Detection and Diagnosis

Abhinav Deshmukh

doi:10.36676/urr.v11.i3.1284

Authors

Dr. Abhinav Deshmukh Associate Professor Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh

DOI:

https://doi.org/10.36676/urr.v11.i3.1284

Keywords:

Artificial Intelligence, Medical Imaging, Deep Learning

Abstract

The integration of artificial intelligence (AI) and deep learning techniques into medical imaging has revolutionized disease detection and diagnosis. This paper provides a comprehensive overview of the applications of deep learning in medical imaging and its impact on healthcare. The paper begins with an introduction to the fundamentals of deep learning, emphasizing convolutional neural networks (CNNs) and their relevance in analyzing medical images. It then explores various applications of deep learning in medical imaging, including automated disease detection and classification, image segmentation for precise anatomical localization, quantitative analysis for predictive modeling, personalized medicine, and workflow optimization. Case studies and examples from different medical specialties, such as oncology, cardiology, and neurology, are presented to illustrate the practical implementation and effectiveness of AI-driven approaches.

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