Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Michael McNitt-Gray"'
Autor:
Michael Lauria, Bradley Stiehl, Anand Santhanam, Dylan O’Connell, Louise Naumann, Michael McNitt-Gray, Ann Raldow, Jonathan Goldin, Igor Barjaktarevic, Daniel A. Low
Publikováno v:
Frontiers in Medicine, Vol 10 (2023)
PurposeRecent advancements in obtaining image-based biomarkers from CT images have enabled lung function characterization, which could aid in lung interventional planning. However, the regional heterogeneity in these biomarkers has not been well docu
Externí odkaz:
https://doaj.org/article/36db664168264d59a631ea8cd4031bf9
Autor:
Miwa Okumura, Takamasa Ota, Kazuhisa Kainuma, James W. Sayre, Michael McNitt-Gray, Kazuhiro Katada
Publikováno v:
International Journal of Biomedical Imaging, Vol 2008 (2008)
Objective. For the multislice CT (MSCT) systems with a larger number of detector rows, it is essential to employ dose-reduction techniques. As reported in previous studies, edge-preserving adaptive image filters, which selectively eliminate only the
Externí odkaz:
https://doaj.org/article/1c2b87f6080c4630927b5329dee27946
Publikováno v:
Medical Physics.
Autor:
Natalie M. Baughan, Heather Whitney, Karen Drukker, Berkman Sahiner, Tingting Hu, Grace Kim, Michael McNitt-Gray, Kyle J. Myers, Maryellen L. Giger
Publikováno v:
Medical Imaging 2023: Imaging Informatics for Healthcare, Research, and Applications.
Autor:
Dallas Tada, Pangyu Teng, Michael McNitt-Gray, Grace H. Kim, Matthew S. Brown, Jonathan Goldin, Kalyani Vyapari, Ashley Banola
Publikováno v:
Medical Imaging 2023: Computer-Aided Diagnosis.
Publikováno v:
Medical Imaging 2023: Computer-Aided Diagnosis.
Publikováno v:
Medical Imaging 2023: Computer-Aided Diagnosis.
Publikováno v:
7th International Conference on Image Formation in X-Ray Computed Tomography.
Autor:
Junyuan Li, Wenying Wang, Matthew Tivnan, Jeremias Sulam, Jerry L. Prince, Michael McNitt-Gray, Joseph W. Stayman, Grace J. Gang
Publikováno v:
Proc SPIE Int Soc Opt Eng
The rapid development of deep-learning methods in medical imaging has called for an analysis method suitable for non-linear and data-dependent algorithms. In this work, we investigate a local linearity analysis where a complex neural network can be r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19d8d18c9a17a2ae8553b1915ab8c3c1
https://europepmc.org/articles/PMC9621688/
https://europepmc.org/articles/PMC9621688/
Publikováno v:
Medical Imaging 2022: Physics of Medical Imaging.