Breaking tunnel vision, imaging AI lifts fluorescence image restoration accuracy and speed

Recent years have witnessed great advances in applying deep learning to improve fluorescence microscopy imaging. However, enhancing the fidelity of image restoration networks and improving their ...
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 ...
GitHub

Cut and Learn for Unsupervised Image & Video Object Detection and Instance Segmentation

We propose MaskCut approach to generate pseudo-masks for multiple objects in an image. CutLER can learn unsupervised object detectors and instance segmentors solely on ImageNet-1K. CutLER exhibits ...
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

Real-Time Cerebral Vessel Segmentation in Laser Speckle Contrast Image Based on Unsupervised Domain Adaptation

Laser speckle contrast imaging (LSCI) is a full-field, high spatiotemporal resolution and low-cost optical technique for measuring blood flow, which has been successfully used for neurovascular ...
Scientific Research Publishing

Semantic Constraint Based Unsupervised Domain Adaptation for Cardiac Segmentation ()

1 College of Science, Shanghai University, Shanghai, China. 2 School of Computer Science and Technology, East China Normal University, Shanghai, China. 3 Shanghai Electric Central Research Institute, ...
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 ...