Gynecological Disease Diagnosis System Based on YOLOv8

To meet the needs of image analysis in gynecological laboratory medicine, the traditional gynecological health monitoring methods have encountered bottlenecks and challenges in medical imaging diagnosis. Because traditional methods rely on manual testing and pathological image analysis, requires a lot of time and professional knowledge, so there is a time consuming and subjectivity strong problem, urgent need for more effective solutions. Based on this background, we have adopted advanced deep learning technology, designed and implemented a system that can automatically extract the features, detection, classification and a variety of department of gynecology common pathological image segmentation. The system in experiments showed high accuracy and efficiency, as the doctor provides a rapid and accurate pathological image analysis platform. The findings are expected to provide automation and accurate diagnosis of disease of department of gynaecology important support, promote the improvement of the level of medical diagnosis, treatment effect is of great significance to the improvement of patients.