Unsupervised domain adaptation (UDA) via deep learning has attracted appealing attention for tackling domain-shift problems caused by distribution discrepancy across different …
Optical coherence tomography angiography (OCT-A) provides depth-resolved visualization of the retinal microvasculature without intravenous dye injection. It facilitates investigations …
S Kumari, P Singh - Computers in Biology and Medicine, 2023 - Elsevier
Deep learning has demonstrated remarkable performance across various tasks in medical imaging. However, these approaches primarily focus on supervised learning, assuming that …
Z Chen, Y Pan, Y Ye, M Lu… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
Distribution shift widely exists in medical images acquired from different medical centres and poses a significant obstacle to deploying the pre-trained semantic segmentation model in …
R Wen, H Yuan, D Ni, W Xiao… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
In medical image segmentation, domain generalization poses a significant challenge due to domain shifts caused by variations in data acquisition devices and other factors. These shifts …
Deep learning (DL) based methods have been extensively studied for medical image segmentation, mostly emphasizing the design and training of DL networks. Only few …
J Cao, HC Yip, Y Chen, M Scheppach, X Luo… - Nature …, 2023 - nature.com
Recent advancements in artificial intelligence have witnessed human-level performance; however, AI-enabled cognitive assistance for therapeutic procedures has not been fully …
Continual test-time adaptation (CTTA) aims to continuously adapt a source-trained model to a target domain with minimal performance loss while assuming no access to the source …
M Ryabkov, M Sizov, E Bederina, P Zarubenko… - Life, 2023 - mdpi.com
(1) Introduction. The problem that limits the intraoperative use of OCTA for the intestinal circulation diagnostics is the low informative value of OCTA images containing too many …