Miteshkumar S — Machine Learning freelancer in Ahmedabad

This project involved creating a high-precision surgical tool segmentation solution tailored for operation room environments. The initial phase included extensive annotation of surgical instruments, with labels applied to specific parts such as shafts, tips, blades, and sutures across video frames and medical images. The annotations were carried out using professional labeling tools to ensure pixel-level accuracy. Using this labeled dataset, a segmentation model was developed in C++, optimized for real-time performance and accuracy. The system integrates with surgical video pipelines and can automatically segment tools as procedures are being conducted. Robust validation and testing were performed to meet the precision and latency demands required in medical AI applications. This solution aids in surgical automation, robotics, and post-operative analysis, bringing efficiency and accuracy to clinical workflows.