Geometric and dosimetric analysis of CT- and MR-based automatic contouring for the EPTN contouring atlas in neuro-oncology.

Femke Vaassen¹, Catharina M L Zegers², David Hofstede², Mart Wubbels², Hilde Beurskens², Lindsey Verheesen², Richard Canters², Padraig Looney³, Michael Battye³, Mark J Gooding³, Inge Compter², Daniëlle B P Eekers², Wouter van Elmpt²

¹Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre(+), Maastricht, the Netherlands. Electronic address: femke.vaassen@maastro.nl.

²Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Centre(+), Maastricht, the Netherlands.

³Mirada Medical Ltd., Oxford, United Kingdom.

PubMed DOI

Abstract

PURPOSE: Atlas-based and deep-learning contouring (DLC) are methods for automatic segmentation of organs-at-risk (OARs). The European Particle Therapy Network (EPTN) published a consensus-based atlas for delineation of OARs in neuro-oncology. In this study, geometric and dosimetric evaluation of automatically-segmented neuro-oncological OARs was performed using CT- and MR-models following the EPTN…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free Account Sign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.