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Automated temporalis muscle quantification and growth charts for children through adulthood.

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Title: Automated temporalis muscle quantification and growth charts for children through adulthood.
Authors: Zapaishchykova A; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Liu KX; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Saraf A; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Ye Z; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Catalano PJ; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA.; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA., Benitez V; Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA., Ravipati Y; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Jain A; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Huang J; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Hayat H; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.; Michigan State University, East Lansing, MI, USA., Likitlersuang J; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Vajapeyam S; Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA.; Department of Radiology, Boston Children's Hospital, Boston, MA, USA., Chopra RB; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Familiar AM; Children's Hospital of Philadelphia, Philadelphia, USA.; University of Pennsylvania, Pennsylvania, USA., Nabavidazeh A; Children's Hospital of Philadelphia, Philadelphia, USA.; University of Pennsylvania, Pennsylvania, USA., Mak RH; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Resnick AC; Children's Hospital of Philadelphia, Philadelphia, USA.; University of Pennsylvania, Pennsylvania, USA., Mueller S; Department of Neurology, Neurosurgery and Pediatrics, University of California, San Francisco, USA., Cooney TM; Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA., Haas-Kogan DA; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Poussaint TY; Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA.; Department of Radiology, Boston Children's Hospital, Boston, MA, USA., Aerts HJWL; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.; Department of Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, the Netherlands., Kann BH; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA. Benjamin_Kann@dfci.harvard.edu.; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA. Benjamin_Kann@dfci.harvard.edu.
Source: Nature communications [Nat Commun] 2023 Nov 09; Vol. 14 (1), pp. 6863. Date of Electronic Publication: 2023 Nov 09.
Publication Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:2041-1723
DOI:10.1038/s41467-023-42501-1