Zobrazeno 1 - 10
of 12 613
pro vyhledávání: '"Albert, J. P."'
Autor:
Ansari, Rayan, Cao, John, Bandyopadhyay, Sabyasachi, Narayan, Sanjiv M., Rogers, Albert J., Pilanci, Mert
We present ConvexECG, an explainable and resource-efficient method for reconstructing six-lead electrocardiograms (ECG) from single-lead data, aimed at advancing personalized and continuous cardiac monitoring. ConvexECG leverages a convex reformulati
Externí odkaz:
http://arxiv.org/abs/2409.12493
Autor:
Xie, Huidong, Guo, Liang, Velo, Alexandre, Liu, Zhao, Liu, Qiong, Guo, Xueqi, Zhou, Bo, Chen, Xiongchao, Tsai, Yu-Jung, Miao, Tianshun, Xia, Menghua, Liu, Yi-Hwa, Armstrong, Ian S., Wang, Ge, Carson, Richard E., Sinusas, Albert J., Liu, Chi
Rb-82 is a radioactive isotope widely used for cardiac PET imaging. Despite numerous benefits of 82-Rb, there are several factors that limits its image quality and quantitative accuracy. First, the short half-life of 82-Rb results in noisy dynamic fr
Externí odkaz:
http://arxiv.org/abs/2409.11543
Autor:
Zhai, Albert J., Shen, Yuan, Chen, Emily Y., Wang, Gloria X., Wang, Xinlei, Wang, Sheng, Guan, Kaiyu, Wang, Shenlong
Can computers perceive the physical properties of objects solely through vision? Research in cognitive science and vision science has shown that humans excel at identifying materials and estimating their physical properties based purely on visual app
Externí odkaz:
http://arxiv.org/abs/2404.04242
Publikováno v:
Phys. Rev. Research 6 (2024) 033257
For the solution of time-dependent nonlinear differential equations, we present variational quantum algorithms (VQAs) that encode both space and time in qubit registers. The spacetime encoding enables us to obtain the entire time evolution from a sin
Externí odkaz:
http://arxiv.org/abs/2403.16791
Autor:
Miao, Albert J., Lin, Shan, Lu, Jingpei, Richter, Florian, Ostrander, Benjamin, Funk, Emily K., Orosco, Ryan K., Yip, Michael C.
Hemorrhaging occurs in surgeries of all types, forcing surgeons to quickly adapt to the visual interference that results from blood rapidly filling the surgical field. Introducing automation into the crucial surgical task of hemostasis management wou
Externí odkaz:
http://arxiv.org/abs/2403.16286
Humans and animals can recognize latent structures in their environment and apply this information to efficiently navigate the world. However, it remains unclear what aspects of neural activity contribute to these computational capabilities. Here, we
Externí odkaz:
http://arxiv.org/abs/2402.16770
Autor:
Guo, Xueqi, Shi, Luyao, Chen, Xiongchao, Liu, Qiong, Zhou, Bo, Xie, Huidong, Liu, Yi-Hwa, Palyo, Richard, Miller, Edward J., Sinusas, Albert J., Staib, Lawrence H., Spottiswoode, Bruce, Liu, Chi, Dvornek, Nicha C.
Inter-frame motion in dynamic cardiac positron emission tomography (PET) using rubidium-82 (82-Rb) myocardial perfusion imaging impacts myocardial blood flow (MBF) quantification and the diagnosis accuracy of coronary artery diseases. However, the hi
Externí odkaz:
http://arxiv.org/abs/2402.09567
Autor:
Chen, Xiongchao, Zhou, Bo, Guo, Xueqi, Xie, Huidong, Liu, Qiong, Duncan, James S., Sinusas, Albert J., Liu, Chi
Single-Photon Emission Computed Tomography (SPECT) is widely applied for the diagnosis of coronary artery diseases. Low-dose (LD) SPECT aims to minimize radiation exposure but leads to increased image noise. Limited-view (LV) SPECT, such as the lates
Externí odkaz:
http://arxiv.org/abs/2401.13140
Autor:
Zhang, Xiaoran, Stendahl, John C., Staib, Lawrence, Sinusas, Albert J., Wong, Alex, Duncan, James S.
We propose an adaptive training scheme for unsupervised medical image registration. Existing methods rely on image reconstruction as the primary supervision signal. However, nuisance variables (e.g. noise and covisibility), violation of the Lambertia
Externí odkaz:
http://arxiv.org/abs/2312.00837
Autor:
Zhang, Xiaoran, Pak, Daniel H., Ahn, Shawn S., Li, Xiaoxiao, You, Chenyu, Staib, Lawrence H., Sinusas, Albert J., Wong, Alex, Duncan, James S.
Deep learning methods for unsupervised registration often rely on objectives that assume a uniform noise level across the spatial domain (e.g. mean-squared error loss), but noise distributions are often heteroscedastic and input-dependent in real-wor
Externí odkaz:
http://arxiv.org/abs/2312.00836