Overview
This subset supports research in volumetric medical image segmentation, tumor classification, and multi-modal learning. By capturing perfusion and vascular features in three dimensions, OTU_3D provides rich structural and functional information for advancing tumor characterization and aiding in the development of robust deep learning models.
This dataset derives from Kaggle and is one of the more widely used public ovarian ultrasound datasets for medical imaging and AI research, particularly for tumor segmentation and classification tasks.
The 3D data represent 170 CEUS (contrast-enhanced ultrasound) images with annotations and labels suitable for machine learning.