The integration of Computer Vision (CV) into healthcare has revolutionized medical imaging, diagnostics, and treatment planning. This chapter explores the evolution of CV from early rule-based systems to modern deep learning-driven approaches. It covers fundamental CV techniques, including object detection, segmentation, classification, mapping and tracking, and explainability, which are the foundational blocks of many medical applications. Key healthcare applications discussed include medical imaging analysis, pathology, ophthalmology, and patient monitoring and rehabilitation, where CV enhances disease detection, treatment planning, and patient care. Overall, this chapter provides a comprehensive overview of CV s role in healthcare, addressing methodologies, applications, and challenges. As deep learning and privacy-preserving techniques evolve, CV is poised to further improve diagnostic accuracy, personalize treatments, and enhance healthcare accessibility in the era of precision medicine.