Dataset of 3D ultrasound neuroimages and Supporting info

We explore methods for data augmentation in neuroimaging. Specifically, we investigate the use of 3D Transfontanellar Ultrasound (3D US) for augmenting 2D datasets of neonatal neuroimages, and we also synthesize an artificial dataset of images using Generative Adversarial Networks (GANs). This dataset consists on 2D slices of 3D US of the brain of neonates which has been successfully used to train an unconditional GAN for generating 2D US images as described in the presentation with DOI: 10.5281/zenodo.14917011本研究探索神经影像学领域的数据增强方法。具体而言，本研究探究使用3D经囟门超声（3D Transfontanellar Ultrasound，3D US）对新生儿神经影像二维数据集进行增强的方案，同时还利用生成对抗网络（Generative Adversarial Networks，GANs）合成人工图像数据集。 本数据集包含新生儿脑部3D经囟门超声的二维切片，该数据集已成功用于训练无条件生成对抗网络，以生成二维超声图像，相关细节详见DOI：10.5281/zenodo.14917011的报告。