DIGITAL IMAGE ANALYSIS AND DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE–BASED MOBILE MEDICAL APPLICATION FOR VISUAL DETECTION OF BLOOD VESSELS

Abstract

The rapid development of digital technologies has significantly transformed modern healthcare systems. Among these advancements, artificial intelligence (AI) and digital image processing technologies have become essential tools for improving diagnostic accuracy and efficiency. Early detection of vascular diseases is critical because cardiovascular disorders remain one of the leading causes of mortality worldwide. This study focuses on the development of a mobile medical application capable of visually detecting blood vessels using digital image analysis and artificial intelligence techniques. The research explores the theoretical foundations and practical implementation of image processing algorithms, deep learning models, and convolutional neural networks for the automatic identification of vascular structures in medical images. The proposed system integrates a mobile platform with AI-based diagnostic capabilities, enabling rapid analysis of images captured by smartphone cameras or medical imaging devices. The study also examines the architecture of the mobile application, its functional modules, and its potential role in telemedicine and remote healthcare services. Experimental results indicate that AI-based image analysis significantly improves the accuracy of vascular detection and reduces diagnostic time. The findings demonstrate that integrating artificial intelligence with mobile health technologies can enhance early diagnosis, support clinical decision-making, and increase accessibility to healthcare services, particularly in regions with limited medical infrastructure.