Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement

BACKGROUND: Longitudinal measurement of glioma burden with MRI is the basis for treatment response assessment. In this study, we developed a deep learning algorithm that automatically segments abnormal fluid attenuated inversion recovery (FLAIR) hyperintensity and contrast-enhancing tumor, quantitat...

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Detalles Bibliográficos
Autores principales: Chang, Ken, Beers, Andrew L, Bai, Harrison X, Brown, James M, Ly, K Ina, Li, Xuejun, Senders, Joeky T, Kavouridis, Vasileios K, Boaro, Alessandro, Su, Chang, Bi, Wenya Linda, Rapalino, Otto, Liao, Weihua, Shen, Qin, Zhou, Hao, Xiao, Bo, Wang, Yinyan, Zhang, Paul J, Pinho, Marco C, Wen, Patrick Y, Batchelor, Tracy T, Boxerman, Jerrold L, Arnaout, Omar, Rosen, Bruce R, Gerstner, Elizabeth R, Yang, Li, Huang, Raymond Y, Kalpathy-Cramer, Jayashree
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Basic and Translational Investigations
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6827825/
https://www.ncbi.nlm.nih.gov/pubmed/31190077
http://dx.doi.org/10.1093/neuonc/noz106

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6827825/
https://www.ncbi.nlm.nih.gov/pubmed/31190077
http://dx.doi.org/10.1093/neuonc/noz106

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