Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Pang, Kaifeng"'
Autor:
Hung, Alex Ling Yu, Zheng, Haoxin, Zhao, Kai, Pang, Kaifeng, Terzopoulos, Demetri, Sung, Kyunghyun
Current deep learning-based models typically analyze medical images in either 2D or 3D albeit disregarding volumetric information or suffering sub-optimal performance due to the anisotropic resolution of MR data. Furthermore, providing an accurate un
Externí odkaz:
http://arxiv.org/abs/2407.01146
Autor:
Hung, Alex Ling Yu, Zheng, Haoxin, Zhao, Kai, Du, Xiaoxi, Pang, Kaifeng, Miao, Qi, Raman, Steven S., Terzopoulos, Demetri, Sung, Kyunghyun
A large portion of volumetric medical data, especially magnetic resonance imaging (MRI) data, is anisotropic, as the through-plane resolution is typically much lower than the in-plane resolution. Both 3D and purely 2D deep learning-based segmentation
Externí odkaz:
http://arxiv.org/abs/2311.04942
Denoising diffusion probabilistic models (DDPMs) have achieved impressive performance on various image generation tasks, including image super-resolution. By learning to reverse the process of gradually diffusing the data distribution into Gaussian n
Externí odkaz:
http://arxiv.org/abs/2307.11926
Autor:
Zhao, Kai1 (AUTHOR) kz@kaizhao.net, Pang, Kaifeng2 (AUTHOR) kaifengpang@mednet.ucla.edu, Hung, Alex LingYu3 (AUTHOR) alexhung96@ucla.edu, Zheng, Haoxin3 (AUTHOR) hzheng@mednet.ucla.edu, Yan, Ran4 (AUTHOR) ranyan@mednet.ucla.edu, Sung, Kyunghyun1 (AUTHOR)
Publikováno v:
Cancers. Sep2024, Vol. 16 Issue 17, p2983. 20p.
The prediction of microsatellite instability (MSI) and microsatellite stability (MSS) is essential in predicting both the treatment response and prognosis of gastrointestinal cancer. In clinical practice, a universal MSI testing is recommended, but t
Externí odkaz:
http://arxiv.org/abs/2201.04769
Publikováno v:
IEEE transactions on medical imaging [IEEE Trans Med Imaging] 2024 Oct 17; Vol. PP. Date of Electronic Publication: 2024 Oct 17.
Autor:
Yu Hung AL; University of California, Los Angeles., Zheng H; University of California, Los Angeles., Zhao K; University of California, Los Angeles., Du X; University of California, Los Angeles., Pang K; University of California, Los Angeles., Miao Q; University of California, Los Angeles., Raman SS; University of California, Los Angeles., Terzopoulos D; University of California, Los Angeles., Sung K; University of California, Los Angeles.
Publikováno v:
IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision [IEEE Winter Conf Appl Comput Vis] 2024 Jan; Vol. 2024, pp. 5911-5920. Date of Electronic Publication: 2024 Apr 09.