Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data.

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@article{d88fb745f7d04a959692f1f240d456e5,

title = "Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data.",

author = "Christina Schwarz-Gsaxner and PM Roth and J{\"u}rgen Wallner and Jan Egger",

year = "2019",

doi = "10.1371/journal.pone.0212550",

language = "English",

journal = "PLOS ONE",

issn = "1932-6203",

publisher = "Public Library of Science",

}

TY - JOUR

T1 - Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data.

AU - Roth, PM

AU - Wallner, Jürgen

A2 - Schwarz-Gsaxner, Christina

A2 - Egger, Jan

PY - 2019

Y1 - 2019

UR - https://www.webofscience.com/wos/woscc/full-record/WOS:000460371800008

UR - https://pubmed.ncbi.nlm.nih.gov/30835746

UR - https://pmc.ncbi.nlm.nih.gov/articles/PMC6400332

U2 - 10.1371/journal.pone.0212550

DO - 10.1371/journal.pone.0212550

M3 - Research article

C2 - 30835746

SN - 1932-6203

JO - PLOS ONE

JF - PLOS ONE

ER -