Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Leiyuan Ma"'
Publikováno v:
International Journal of Hyperthermia, Vol 41, Iss 1 (2024)
Objective A radiomics nomogram will be created utilizing MRI data from intratumoral and peritumoral areas to forecast survival outcomes in patients who have had treatment for pancreatic ductal adenocarcinoma (PDAC).Methods A total of 87 individuals d
Externí odkaz:
https://doaj.org/article/8e04fd7cfbd34c44a354cb4d6940d86f
Autor:
Changjie Shao, Juntao Zhang, Jing Guo, Liang Zhang, Yuhan Zhang, Leiyuan Ma, Chuanxin Gong, Yaqi Tian, Jingjing Chen, Ning Yu
Publikováno v:
International Journal of Hyperthermia, Vol 40, Iss 1 (2023)
AbstractObjective To develop and validate a radiomics nomogram for predicting the survival of patients with pancreatic ductal adenocarcinoma (PDAC) after receiving high-intensity focused ultrasound (HIFU) treatment.Methods A total of 52 patients with
Externí odkaz:
https://doaj.org/article/d4a639370d1344d98028bc20f14fc9da
Publikováno v:
Abdominal Radiology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d19cdd58a685e47033e594a3dd04a1ef
https://doi.org/10.1007/s00261-022-03780-2
https://doi.org/10.1007/s00261-022-03780-2
Purpose: The risk factors of chronic kidney disease were analyzed by using the region of interest quantitative technology of color doppler combined with QLab software, and a Nomogram was established to conduct an individualized assessment of patients
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2320e95de0224880e1d4bac7fced291
https://doi.org/10.21203/rs.3.rs-989353/v1
https://doi.org/10.21203/rs.3.rs-989353/v1
Publikováno v:
Abdominal radiology (New York). 47(12)
The risk factors of chronic kidney disease were analyzed by using the region of interest quantitative technology of color Doppler combined with QLab software, and a Nomogram was established to conduct an individualized assessment of patients with chr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cef18cf0475f07a5d589c2e9f9e62596
https://pubmed.ncbi.nlm.nih.gov/36121456
https://pubmed.ncbi.nlm.nih.gov/36121456
Publikováno v:
ICIP
Semantic segmentation is a challenging computer visual task which needs enormous pixel-level annotation data. But collecting a large amount of pixel-level annotation data is labor intensive. To address this issue, our work focuses on weakly-supervise
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8efba6653a92aee4900180758dbe0af8
https://doi.org/10.1109/icip.2019.8803111
https://doi.org/10.1109/icip.2019.8803111