IEEE

Unsupervised Domain Adaptation for Medical Image Segmentation by Disentanglement Learning and Self-Training

Abstract: Unsupervised domain adaption (UDA), which aims to enhance the segmentation performance of deep models on unlabeled data, has recently drawn much attention. In this paper, we propose a novel ...
IEEE

Contrastive Registration for Unsupervised Medical Image Segmentation

Abstract: Medical image segmentation is an important task in medical imaging, as it serves as the first step for clinical diagnosis and treatment planning. While major success has been reported using ...
Frontiers

Evaluation of MRI Denoising Methods Using Unsupervised Learning

In this paper we evaluate two unsupervised approaches to denoise Magnetic Resonance Images (MRI) in the complex image space using the raw information that k-space holds. The first method is based on ...
Scientific Research Publishing

Ultrasonographic Segmentation of Fetal Lung with Deep Learning ()

1 Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China. 2 Department of Medical Ultrasound, Fudan University Shanghai Cancer Center; ...