Deep Learning CT-based Quantitative Visualization Tool for Liver Volume Estimation: Defining Normal and Hepatomegaly

Alberto A. Perez, Victoria Noe-Kim, Meghan G. Lubner, Peter M. Graffy, John W. Garrett, Daniel C. Elton, Ronald M. Summers, Perry J. Pickhardt

Open source

DOI: 10.1148/radiol.2021210531
Published: 2022-01
Container: Radiology
Publisher: Radiological Society of North America (RSNA)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1148/radiol.2021210531,
  title = {Deep Learning CT-based Quantitative Visualization Tool for Liver Volume Estimation: Defining Normal and Hepatomegaly},
  author = {Alberto A. Perez and Victoria Noe-Kim and Meghan G. Lubner and Peter M. Graffy and John W. Garrett and Daniel C. Elton and Ronald M. Summers and Perry J. Pickhardt},
  year = {2022},
  journal = {Radiology},
  doi = {10.1148/radiol.2021210531},
  url = {https://doi.org/10.1148/radiol.2021210531}
}

RIS

TY  - JOUR
TI  - Deep Learning CT-based Quantitative Visualization Tool for Liver Volume Estimation: Defining Normal and Hepatomegaly
AU  - Alberto A. Perez
AU  - Victoria Noe-Kim
AU  - Meghan G. Lubner
AU  - Peter M. Graffy
AU  - John W. Garrett
AU  - Daniel C. Elton
AU  - Ronald M. Summers
AU  - Perry J. Pickhardt
PY  - 2022
JO  - Radiology
DO  - 10.1148/radiol.2021210531
UR  - https://doi.org/10.1148/radiol.2021210531
ER  -

APA

Perez, A. A., Noe-Kim, V., Lubner, M. G., Graffy, P. M., Garrett, J. W., Elton, D. C., Summers, R. M., & Pickhardt, P. J. (2022). Deep Learning CT-based Quantitative Visualization Tool for Liver Volume Estimation: Defining Normal and Hepatomegaly. Radiology. https://doi.org/10.1148/radiol.2021210531

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crossref · retrieved 2026-09-26T17:32:44.761Z