Saak Transform-Based Machine Learning for Light-Sheet Imaging of Cardiac Trabeculation

OBJECTIVE: Recent advances in light-sheet fluorescence microscopy (LSFM) enable 3-dimensional (3-D) imaging of cardiac architecture and mechanics in toto. However, segmentation of the cardiac trabecular network to quantify cardiac injury remains a challenge. METHODS: We hereby employed “subspace app...

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I publikationen:IEEE Trans Biomed Eng
Huvudupphovsmän: Ding, Yichen, Gudapati, Varun, Lin, Ruiyuan, Fei, Yanan, Sevag Packard, René R, Song, Sibo, Chang, Chih-Chiang, Baek, Kyung In, Wang, Zhaoqiang, Roustaei, Mehrdad, Kuang, Dengfeng, Jay Kuo, C.-C., Hsiai, Tzung K.
Materialtyp: Artigo
Språk:Inglês
Publicerad: 2020
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Article
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC7606319/
https://ncbi.nlm.nih.gov/pubmed/32365015
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TBME.2020.2991754
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