… Deep learning-based methods have recently achieved … domain adaptation methods. We
also aim to extend our framework to other medical image segmentation tasks (eg, brain image …

… Additionally, we use a decoder network to make target images and target predictions … , we
extend our unsupervised domain adaptation technique to semi-supervised domain adaptation (…

… on Medical Image … Unsupervised domain adaptation in brain lesion segmentation with
adversarial networks. In International Conference on Information Processing in Medical Imaging, …

… However, state-of-theart deep learning models still suffer from significant performance drops
… spirit to recent advances in self-supervised contrastive learning, which pulls an image to be …

… Recent advances in deep neural networks make it possible to … of the current studies using
deep learning methods is that it is … vised domain adaptation for medical imaging segmentation …

… extra annotations for medical images, which leads to the … Recent advances on unsupervised
domain adaptation can be summarized as image alignment [16]–[21] using image-to-image …

… these recent studies to provide a comprehensive overview of applying deep learning
methods in various medical image analysis tasks. Especially, we emphasize the latest progress …

… More recently, with the advancement of generative … aim at our topic of unsupervised domain
adaptation of CNNs, … 3D CNNs in domain adaptation for medical image segmentation task, …

… Deep Learning has achieved remarkable performance in various computer vision tasks,
such as image … Taking medical imaging for instance, each image of the Diabetic Retinopathy …

… of deep neural networks, recent remarkable achievements in UDA resort to learning domain-…
UDA is the key machine learning topic to deal with this dilemma [2]. On the other hand, …