Work

Quantifying and visualising uncertainty in deep learning-based segmentation for radiation therapy treatment planning: What do radiation oncologists and therapists want?

Year: 2024

Type: article

Source: Radiotherapy and Oncology

DOI: 10.1016/j.radonc.2024.110545

Authors: M. Huet-Dastarac, N.M.C. van Acht, F.C. Maruccio, J.E. van Aalst, J.C.J. van Oorschodt, F. Cnossen, T.M. Janssen, C.L. Brouwer, A. Barragan Montero, C.W. Hurkmans

Institutions: UCLouvain, Catharina Ziekenhuis, Eindhoven University of Technology, The Netherlands Cancer Institute, University Medical Center Groningen, University of Groningen, University of Twente

Language: English

Topic: Advanced Radiotherapy Techniques

Subfield: Radiation

Field: Physics and Astronomy

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: Université Catholique de Louvain, Elekta, Fédération Wallonie-Bruxelles, Fonds Spéciaux de Recherche

OpenAlex ID: W4402788412

FWCI: 4.012

Cites: 55

Cited by: 14

Related to: 10