Identifying radiotherapy target volumes in brain cancer by image analysis-Reference-Cited by-同舟云学术

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Identifying radiotherapy target volumes in brain cancer by image analysis

Published:2015-10 Issue:5 Volume:2 Page:123-128
ISSN:2053-3713
Container-title:Healthcare Technology Letters
language:en
Short-container-title:Healthcare Technology Letters

Author:

Cheng Kun¹,Montgomery Dean¹^ORCID,Feng Yang¹,Steel Robin¹,Liao Hanqing²,McLaren Duncan B.³,Erridge Sara C.³,McLaughlin Stephen⁴,Nailon William H.¹⁵

Affiliation:

1. Department of Oncology Physics Edinburgh Cancer Centre, Western General Hospital Crewe Road South Edinburgh EH4 2XU UK

2. Department of Electrical Engineering and Electronics University of Liverpool Liverpool L69 3GQ UK

3. Department of Clinical Oncology Edinburgh Cancer Centre, Western General Hospital Crewe Road South Edinburgh EH4 2XU UK

4. School of Engineering and Physical Sciences Heriot Watt University David Brewster Building Edinburgh EH14 4AS UK

5. School of Engineering University of Edinburgh King's Buildings, Mayfield Road Edinburgh EH9 3JL UK

Publisher

Institution of Engineering and Technology (IET)

Subject

Health Information Management,Health Informatics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/htl.2015.0014

Reference44 articles.

1. Brain Tumors

2. Cancer Research UK: ‘Cancer stats report – brain other CNS and intracranial tumours key facts’ January2014

3. Long-term survival with glioblastoma multiforme

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1. Response to Letter to the Editor of Radiotherapy and Oncology regarding the paper entitled “50 years of radiotherapy research: Evolution, trends and lessons for the future“ by Berger et al. (December 2021, volume 165);Radiotherapy and Oncology;2022-07

2. Magnetic resonance spectroscopic imaging in gliomas: clinical diagnosis and radiotherapy planning;BJR|Open;2020-11

3. Breath markers for therapeutic radiation;Journal of Breath Research;2020-10-24

4. Fully automated brain resection cavity delineation for radiation target volume definition in glioblastoma patients using deep learning;Radiation Oncology;2020-05-06

5. Real-time and multimodal brain slice-to-volume registration using CNN;Expert Systems with Applications;2019-11

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