Auto‐segmentation of organs at risk for head and neck radiotherapy planning: From atlas‐based to deep learning methods-Reference-Cited by-同舟云学术

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Auto‐segmentation of organs at risk for head and neck radiotherapy planning: From atlas‐based to deep learning methods

Published:2020-07-28 Issue:9 Volume:47 Page:
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Vrtovec Tomaž¹,Močnik Domen¹,Strojan Primož²,Pernuš Franjo¹,Ibragimov Bulat¹³

Affiliation:

1. Faculty Electrical Engineering University of Ljubljana Tržaška cesta 25 Ljubljana SI‐1000 Slovenia

2. Institute of Oncology Ljubljana Zaloška cesta 2 Ljubljana SI‐1000 Slovenia

3. Department of Computer Science University of Copenhagen Universitetsparken 1 Copenhagen D‐2100 Denmark

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.14320

Reference153 articles.

1. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

2. The impact of cancer incidence and stage on optimal utilization of radiotherapy: Methodology of a population based analysis by the ESTRO-HERO project

3. Uncertainties in volume delineation in radiation oncology: A systematic review and recommendations for future studies

4. Autosegmentation of Images in Radiation Oncology

5. Vision 20/20: Perspectives on automated image segmentation for radiotherapy

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4. Deep learning for autosegmentation for radiotherapy treatment planning: State-of-the-art and novel perspectives;Strahlentherapie und Onkologie;2024-08-06

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