A Data Augmentation Pipeline to Generate Synthetic Labeled Datasets of 3D Echocardiography Images using a GAN

arXiv:2403.05384v1 Announce Type: cross
Abstract: Due to privacy issues and limited amount of publicly available labeled datasets in the domain of medical imaging, we propose an image generation pipeline to synthesize 3D echocardiographic images with corresponding ground truth labels, to alleviate the need for data collection and for laborious and error-prone human labeling of images for subsequent Deep Learning (DL) tasks. The proposed method utilizes detailed anatomical segmentations of the heart as ground truth label sources. This initial dataset is …

abstract arxiv augmentation cs.cv data datasets domain eess.iv gan generate image image generation images imaging labels medical medical imaging pipeline privacy synthetic truth type