This paper proposes a novel, unsupervised super-resolution (SR) approach...
This paper presents a super-resolution (SR) method with unpaired trainin...
This paper presents a visualization method of intestine (the small and l...
This paper newly introduces multi-modality loss function for GAN-based
s...
Recent advances in deep learning, like 3D fully convolutional networks
(...
This paper presents a novel unsupervised segmentation method for 3D medi...
This paper presents a novel method for unsupervised segmentation of path...
One of the most common tasks in medical imaging is semantic segmentation...
Recent advances in 3D fully convolutional networks (FCN) have made it
fe...
Deep learning-based methods achieved impressive results for the segmenta...
Pancreas segmentation in computed tomography imaging has been historical...
Automatic multi-organ segmentation of the dual energy computed tomograph...
Computational anatomy allows the quantitative analysis of organs in medi...