Semantic segmentation and detection of mediastinal lymph nodes and anatomical structures in CT data for lung cancer staging

Author:

Bouget David,Jørgensen Arve,Kiss Gabriel,Leira Haakon Olav,Langø Thomas

Funder

Center for Innovative Ultrasound Solutions

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Radiology Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering

Reference14 articles.

1. Falk S, Williams C (2010) Lung cancer-the facts, 3rd edn, chap 1. Oxford University Press, pp 3–4. ISBN 978-0-19-956933-5

2. Schwartz L, Bogaerts J, Ford R, Shankar L, Therasse P, Gwyther S, Eisenhauer EA (2009) Evaluation of lymph nodes with RECIST 1.1. Eur J Cancer 45(2):261–267

3. El-Sherief AH, Lau CT, Wu CC, Drake RL, Abbott GF, Rice TW (2014) International association for the study of lung cancer (IASLC) lymph node map: radiologic review with CT illustration. Radiographics 34(6):1680–1691

4. Sorger H, Hofstad EF, Amundsen T, Lang T, Bakeng JBL, Leira HO (2017) A multimodal image guiding system for navigated ultrasound bronchoscopy (EBUS): a human feasibility study. PLoS ONE 12(2):e0171841

5. Roth HR, Lu L, Seff A, Cherry KM, Hoffman J, Wang S, Liu J, Turkbey E, Summers RM (2014) A new 2.5 D representation for lymph node detection using random sets of deep convolutional neural network observations. In: International conference on medical image computing and computer-assisted intervention. Springer, pp 520–527

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