Abnormal uterine classification based on an improved YOLOv5 framework from ultrasound images

Infertility, a reproductive disorder, arises from various causes, including abnormalities in the uterus and associated reproductive organs, which are significant contributors to the condition. While acupuncture has been proven effective intreating infertility, accurately diagnosing its underlying causes remains a challenge. Ultrasonic imaging, capable of identifying issues such as uterine fibroids, ovarian cysts, and fallopian tube blockages, facilitates the development of more targeted acupuncture treatment plans. This highlights the need for a method that enables acupuncture practitioners with limited exposure to Western medicine to interpret ultrasonic images effectively. The approach introduced in this study leverages the yolov5 framework to classify uterine abnormalities. Results indicate that this method improves baseline performance compared to other methods. This method will enhance clinical diagnosis, aid in pinpointing the causes of infertility, and improve the precision of infertility diagnoses by acupuncture specialists, thereby boosting the efficacy of acupuncture interventions for infertility.