Though they rarely become malignant, the surgical removal of fibroids (uterine myomas) is commonly considered to prevent any possible future risks. As the least invasive intervention, endoscopic surgery is the most popular approach for this aim. However, since these compact tumors reside in the deep (muscle/connective) tissues of the uterus, they are hardly visible using only the video stream provided by the endoscopic camera. Thus, conform to the current general trend in human surgery, in this paper we propose a multimodal approach to make these tumors more visible during endoscopic interventions, namely, the reconstruction of the whole three-dimensional model of the uterus from ultrasound images and segmentation of the fibroids using this modality. Then, we map the result of the segmentation on the surface of the uterus, hence they become visible during endoscopic surgery. Similar efforts have already been made, considering the usage of MRI for this purpose, but ultrasound image acquisition is more widely available, faster, and cheaper next to the lower image quality. Our aim is to use the output of the 3D ultrasound imaging device during the laparoscopic surgery. Our segmentation pipeline processes the ultrasound images and consists of Otsu's thresholding using a special mask derived from image averages and morphological snakes to extract uterus boundary. As the final step, we project the segmented 3D model of the uterus with its lesion on an endoscope camera flow in real time to provide an augmented reality application.