Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Shihan Qiu"'
Autor:
Haoran Sun, Lixia Wang, Timothy Daskivich, Shihan Qiu, Fei Han, Alessandro D'Agnolo, Rola Saouaf, Anthony G. Christodoulou, Hyung Kim, Debiao Li, Yibin Xie
Publikováno v:
Frontiers in Radiology, Vol 3 (2023)
PurposeTo develop a deep learning-based method to retrospectively quantify T2 from conventional T1- and T2-weighted images.MethodsTwenty-five subjects were imaged using a multi-echo spin-echo sequence to estimate reference prostate T2 maps. Conventio
Externí odkaz:
https://doaj.org/article/978f5760de9d4f5a81ec8e8a6d15bbaa
Autor:
Shihan Qiu, Sen Ma, Lixia Wang, Yuhua Chen, Zhaoyang Fan, Franklin G. Moser, Marcel Maya, Pascal Sati, Nancy L. Sicotte, Anthony G. Christodoulou, Yibin Xie, Debiao Li
Publikováno v:
Magnetic Resonance in Medicine.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3dfcb6e99f9c5146265a5c79276d13c3
https://doi.org/10.1002/mrm.29715
https://doi.org/10.1002/mrm.29715
Publikováno v:
2022 China Automation Congress (CAC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd488f336a684dba873e87e0f2db704c
https://doi.org/10.1109/cac57257.2022.10055371
https://doi.org/10.1109/cac57257.2022.10055371
Publikováno v:
2022 China Automation Congress (CAC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c6a6d6b79e63b4e64c55f84c3594cfef
https://doi.org/10.1109/cac57257.2022.10055854
https://doi.org/10.1109/cac57257.2022.10055854
Publikováno v:
Computers in Biology and Medicine. 155:106462
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89dde6d8f82fc1e921a68e22a94477ce
https://doi.org/10.1016/j.compbiomed.2022.106462
https://doi.org/10.1016/j.compbiomed.2022.106462
Publikováno v:
2021 China Automation Congress (CAC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d3b6b317aa5501b261ae7218fd54a6c
https://doi.org/10.1109/cac53003.2021.9728621
https://doi.org/10.1109/cac53003.2021.9728621
Autor:
Zhaoyang Fan, Debiao Li, Marcel M. Maya, Shihan Qiu, Sen Ma, Anthony G. Christodoulou, Yuhua Chen, Yibin Xie, Franklin G. Moser
Publikováno v:
Magn Reson Med
Purpose To develop a deep-learning-based method to quantify multiple parameters in the brain from conventional contrast-weighted images. Methods Eighteen subjects were imaged using an MR Multitasking sequence to generate reference T1 and T2 maps in t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62825e4b09df074c22731d9bf6f25730
https://pubmed.ncbi.nlm.nih.gov/34374468
https://pubmed.ncbi.nlm.nih.gov/34374468