A method to combine target volume data from 3D and 4D planned thoracic radiotherapy patient cohorts for machine learning applications.
Price, Gareth J
Moore, Christopher J
van Herk, Marcel
AffiliationManchester Cancer Research Centre, Division of Molecular and Clinical Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Sciences Centre, UK
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AbstractThe gross tumour volume (GTV) is predictive of clinical outcome and consequently features in many machine-learned models. 4D-planning, however, has prompted substitution of the GTV with the internal gross target volume (iGTV). We present and validate a method to synthesise GTV data from the iGTV, allowing the combination of 3D and 4D planned patient cohorts for modelling.
CitationA method to combine target volume data from 3D and 4D planned thoracic radiotherapy patient cohorts for machine learning applications. 2017 Radiother Oncol
JournalRadiotherapy and Oncology
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