Monte Carlo reference data sets for imaging research: Executive summary of the report of AAPM Research Committee Task Group 195
Ioannis Sechopoulos(Radboud University Nijmegen), Adam C. Turner(University of California, Los Angeles), Ehsan Samei(Duke University), Aldo Badano(United States Food and Drug Administration), Kyle McMillan(University of California, Los Angeles), Iacovos S. Kyprianou(United States Food and Drug Administration), John M. Boone(University of California, Davis), Andreu Badal(United States Food and Drug Administration), Michael F. McNitt‐Gray(SUNY Upstate Medical University), Ernesto Mainegra‐Hing(National Research Council Canada), Elsayed Ali(Ottawa Hospital), D. W. O. Rogers(National Research Council Canada)
Cited by 104
Related Papers
AAPM's TG‐51 protocol for clinical reference dosimetry of high‐energy photon and electron beams
|Medical Physics|1999|1.7k
Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists
|JNCI Journal of the National Cancer Institute|2018|674
Detection of Breast Cancer with Mammography: Effect of an Artificial Intelligence Support System
|Radiology|2018|601
A review of breast tomosynthesis. Part I. The image acquisition process
|Medical Physics|2013|424
Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update
|Radiology Artificial Intelligence|2024|331