Zobrazeno 1 - 10
of 201
pro vyhledávání: '"Guo, Xutao"'
Recent advancements in deep learning have shifted the development of brain imaging analysis. However, several challenges remain, such as heterogeneity, individual variations, and the contradiction between the high dimensionality and small size of bra
Externí odkaz:
http://arxiv.org/abs/2407.16128
A Chebyshev Confidence Guided Source-Free Domain Adaptation Framework for Medical Image Segmentation
Source-free domain adaptation (SFDA) aims to adapt models trained on a labeled source domain to an unlabeled target domain without the access to source data. In medical imaging scenarios, the practical significance of SFDA methods has been emphasized
Externí odkaz:
http://arxiv.org/abs/2310.18087
Convolutional neural networks (CNN) and Transformer variants have emerged as the leading medical image segmentation backbones. Nonetheless, due to their limitations in either preserving global image context or efficiently processing irregular shapes
Externí odkaz:
http://arxiv.org/abs/2305.15911
Since 2019, coronavirus Disease 2019 (COVID-19) has been widely spread and posed a serious threat to public health. Chest Computed Tomography (CT) holds great potential for screening and diagnosis of this disease. The segmentation of COVID-19 CT imag
Externí odkaz:
http://arxiv.org/abs/2302.14277
Accelerating Diffusion Models via Pre-segmentation Diffusion Sampling for Medical Image Segmentation
Based on the Denoising Diffusion Probabilistic Model (DDPM), medical image segmentation can be described as a conditional image generation task, which allows to compute pixel-wise uncertainty maps of the segmentation and allows an implicit ensemble o
Externí odkaz:
http://arxiv.org/abs/2210.17408
Multi-modal neuroimaging technology has greatlly facilitated the efficiency and diagnosis accuracy, which provides complementary information in discovering objective disease biomarkers. Conventional deep learning methods, e.g. convolutional neural ne
Externí odkaz:
http://arxiv.org/abs/2210.13721
The brain age has been proven to be a phenotype of relevance to cognitive performance and brain disease. Achieving accurate brain age prediction is an essential prerequisite for optimizing the predicted brain-age difference as a biomarker. As a compr
Externí odkaz:
http://arxiv.org/abs/2209.08933
Autor:
Guo, Xutao, Li, Xiaojuan, Lei, Jie, Zhang, Yifan, Yue, Shihao, Ma, Haoxin, Long, Wei, Xi, Zengzhe
Publikováno v:
In Ceramics International 1 October 2024 50(19) Part A:35638-35646
Publikováno v:
In Computers in Biology and Medicine September 2024 180
Accurate medical image segmentation is crucial for diagnosis and analysis. However, the models without calibrated uncertainty estimates might lead to errors in downstream analysis and exhibit low levels of robustness. Estimating the uncertainty in th
Externí odkaz:
http://arxiv.org/abs/2109.07045