Zobrazeno 1 - 10
of 176
pro vyhledávání: '"Leslie, Ying"'
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-9 (2023)
The authors develop an imaging-based intelligent spectrometer on a plasmonic “rainbow” chip. It can accurately and precisely determine the spectroscopic and polarimetric information of the illumination spectrum using a single image assisted by su
Externí odkaz:
https://doaj.org/article/32a506a82c424c73a9292f6665346146
Autor:
Wang, Shanshan, Ke, Ziwen, Cheng, Huitao, Jia, Sen, Leslie, Ying, Zheng, Hairong, Liang, Dong
Dynamic MR image reconstruction from incomplete k-space data has generated great research interest due to its capability in reducing scan time. Nevertheless, the reconstruction problem is still challenging due to its ill-posed nature. Most existing m
Externí odkaz:
http://arxiv.org/abs/1810.00302
Autor:
Zifei Liang, Choong H Lee, Tanzil M Arefin, Zijun Dong, Piotr Walczak, Song-Hai Shi, Florian Knoll, Yulin Ge, Leslie Ying, Jiangyang Zhang
Publikováno v:
eLife, Vol 11 (2022)
1H MRI maps brain structure and function non-invasively through versatile contrasts that exploit inhomogeneity in tissue micro-environments. Inferring histopathological information from magnetic resonance imaging (MRI) findings, however, remains chal
Externí odkaz:
https://doaj.org/article/117cd91f4ee44b44b48883685e3d4ba5
Autor:
Umesh C. Sharma, Kanhao Zhao, Kyle Mentkowski, Swati D. Sonkawade, Badri Karthikeyan, Jennifer K. Lang, Leslie Ying
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 8 (2021)
Contrast-enhanced cardiac magnetic resonance imaging (MRI) is routinely used to determine myocardial scar burden and make therapeutic decisions for coronary revascularization. Currently, there are no optimized deep-learning algorithms for the automat
Externí odkaz:
https://doaj.org/article/5a401a72d8224ab6af826dcfd9a95845
Publikováno v:
IEEE Signal Processing Magazine. 40:116-128
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::33e2d90269e446471c5fc8d9146bf411
https://doi.org/10.1109/msp.2023.3236483
https://doi.org/10.1109/msp.2023.3236483
Autor:
Chaoyi Zhang, Tanzil Mahmud Arefin, Ukash Nakarmi, Choong Heon Lee, Hongyu Li, Dong Liang, Jiangyang Zhang, Leslie Ying
Publikováno v:
NeuroImage, Vol 210, Iss , Pp 116584- (2020)
Diffusion Magnetic Resonance Imaging (dMRI) has shown great potential in probing tissue microstructure and structural connectivity in the brain but is often limited by the lengthy scan time needed to sample the diffusion profile by acquiring multiple
Externí odkaz:
https://doaj.org/article/1d34f830aa94452699b490388242020e
Publikováno v:
IEEE Transactions on Biomedical Engineering. 69:2996-3007
In this study, we present a novel method to reconstruct the MR parametric maps from highly undersampled k-space data. Specifically, we utilize a nonlinear model to sparsely represent the unknown MR parameter-weighted images in high-dimensional featur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2782e4a9ce426dd9c0597c2758b2f1c
https://doi.org/10.1109/tbme.2022.3158904
https://doi.org/10.1109/tbme.2022.3158904
Autor:
Haifeng Wang, Yanjie Zhu, Dong Liang, Wenqi Huang, Zhuo-Xu Cui, Leslie Ying, Ziwen Ke, Jing Cheng
Publikováno v:
IEEE Transactions on Medical Imaging. 40:3140-3153
Magnetic resonance (MR) image reconstruction from undersampled k-space data can be formulated as a minimization problem involving data consistency and image prior. Existing deep learning (DL)-based methods for MR reconstruction employ deep networks t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd4b24cbb8bc6cd63a8683f13d980af5
https://doi.org/10.1109/tmi.2021.3096232
https://doi.org/10.1109/tmi.2021.3096232
Autor:
Xin Liu, Yuanyuan Liu, Zhuo-Xu Cui, Yanjie Zhu, Leslie Ying, Weitian Chen, Qingyong Zhu, Hairong Zheng, Dong Liang
Publikováno v:
Quantitative Imaging in Medicine and Surgery. 11:3376-3391
Background Magnetic resonance (MR) quantitative T1ρ imaging has been increasingly used to detect the early stages of osteoarthritis. The small volume and curved surface of articular cartilage necessitate imaging with high in-plane resolution and thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5716e431c9bc657e016d119b35bbc461
https://doi.org/10.21037/qims-20-790
https://doi.org/10.21037/qims-20-790
Autor:
Hongyu Li, Mingrui Yang, Jee Hun Kim, Chaoyi Zhang, Ruiying Liu, Peizhou Huang, Dong Liang, Xiaoliang Zhang, Xiaojuan Li, Leslie Ying
Publikováno v:
Magnetic resonance in medicine. 89(1)
To develop an ultrafast and robust MR parameter mapping network using deep learning.We design a deep learning framework called SuperMAP that directly converts a series of undersampled (both in k-space and parameter-space) parameter-weighted images in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8cde47aa5935ef117700e4677318a2e4
https://pubmed.ncbi.nlm.nih.gov/36128884
https://pubmed.ncbi.nlm.nih.gov/36128884