Endometriosis is a chronic condition where tissue similar to the uterine lining grows outside the uterus, affecting up to 10% of reproductive-aged women. It causes severe pain during periods, sexual intercourse, and other activities, and its diagnosis typically requires invasive methods like laparoscopy and biopsy. Our project aims to develop a model using YOLO v8n to detect endometriosis lesions on the rectum via ultrasound, assisting medical professionals in identifying the condition. The model is trained on 17 ultrasound videos, utilizing cross-validation, data augmentation, and key performance metrics such as precision and recall for classification, and mAP for object detection.