Computer Vision Algorithms for Surgical Assistance in Cloud-Based Telemedicine

In order to improve surgical support, this study investigates the incorporation of algorithmic techniques for computer vision into a stored in-cloud telemedicine platform. We concentrate on the technical facets of this cutting-edge healthcare paradigm using an interpretive ideology and deductive methodology. Utilizing secondary gathering of information from credible sources, an exploratory approach is used. The study assesses the privacy and safety precautions necessary to protect patient data while it is being sent and stored. Access controls, strong encryption techniques, and regular safety inspections are cited as essential elements. These steps promote system confidence by ensuring adherence to laws governing the safeguarding of healthcare data. The research also evaluates the use of algorithms for machine vision for surgical navigation. The algorithms are adept at tracking instruments, identifying anatomical structures, and enhancing visibility, supporting surgical teams throughout real-time. Depth awareness is a key component of precision surgical procedures, and stereoscopic visual abilities improve the sense of depth. Customer acceptance and satisfaction are crucial to the achievement of telemedicine-assisted operation. Both healthcare professionals and patients appreciate the system's use, trustworthiness, and clarity of communication. For a flawless user experience, appropriate technical assistance and training are considered as being essential. In its conclusions, the paper makes suggestions for future research, highlighting the necessity of empirical investigations, sophisticated encryption methods, and the incorporation of cutting-edge technology like AR.