Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Luojie Huang"'
Autor:
Gregory N. McKay, Luojie Huang, Taylor L. Bobrow, Srivathsan Kalyan, Soojung Claire Hur, Sophie Lanzkron, Lydia H. Pecker, Alison R. Moliterno, Nicholas J. Durr
Publikováno v:
Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XX.
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200465
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c43ecd5f94bdc45e3623b4bf80e881d
https://doi.org/10.1007/978-3-031-20047-2_12
https://doi.org/10.1007/978-3-031-20047-2_12
Publikováno v:
Biophotonics Congress: Biomedical Optics 2022 (Translational, Microscopy, OCT, OTS, BRAIN).
3D Attention M-net for Short-axis Left Ventricular Myocardium Segmentation in Mice MR cardiac Images
Autor:
Luojie Huang, Andrew Jin, Jinchi Wei, Dnyanesh Tipre, Chin-Fu Liu, Robert G. Weiss, Siamak Ardekani
Publikováno v:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2021
Small rodent cardiac magnetic resonance imaging (MRI) plays an important role in preclinical models of cardiac disease. Accurate myocardial boundaries delineation is crucial to most morphological and functional analysis in rodent cardiac MRIs. Howeve
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 ISBN: 9783030872366
MICCAI (8)
MICCAI (8)
Oblique back-illumination capillaroscopy has recently been introduced as an efficient method for non-invasive blood cell imaging in human capillaries. To apply this technique to clinical blood cell counting, solutions for automatic processing of acqu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81ee03ceaf35b6821e0aa2b13989177e
https://doi.org/10.1007/978-3-030-87237-3_40
https://doi.org/10.1007/978-3-030-87237-3_40
Publikováno v:
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation. 43(2)
Restless legs syndrome,as a common sleep disorder,has nowadays long been diagnosed by self-rating scale and polysomnography.In this paper,a domestic diagnosis system for early restless legs syndrome based on deep learning is proposed,which is suitabl