T. Dao

SOTS: Leveraging Self-supervised Pretraining for Label-Efficient Ovarian Tumor Segmentation in Ultrasound Images.

A Self-supervised Ovarian Tumor Segmentation (SOTS) framework that leverages unlabeled ultrasound images to learn robust feature representations and achieves segmentation accuracy comparable to fully supervised U-Net variants while requiring substantially fewer annotations is proposed.