UniToChest: A Lung Image Dataset for Segmentation of Cancerous Nodules on CT Scans-Reference-Cited by-同舟云学术

UniToChest: A Lung Image Dataset for Segmentation of Cancerous Nodules on CT Scans

Published:2022 Issue: Volume: Page:185-196
ISSN:0302-9743
Container-title:Image Analysis and Processing – ICIAP 2022
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Author:

Chaudhry Hafiza Ayesha Hoor^ORCID,Renzulli Riccardo^ORCID,Perlo Daniele^ORCID,Santinelli Francesca,Tibaldi Stefano^ORCID,Cristiano Carmen,Grosso Marco^ORCID,Limerutti Giorgio,Fiandrotti Attilio^ORCID,Grangetto Marco^ORCID,Fonio Paolo^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-06427-2_16

Reference22 articles.

1. Armato, S.G., et al.: The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans. Med. Phys. 38(2), 915–931 (2011). https://doi.org/10.1118/1.3528204, https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI

2. EAI/Springer Innovations in Communication and Computing;AH Chaudhary,2019

3. DeepHealth: Deep-learning and HPC to boost biomedical applications for health (2019). https://deephealth-project.eu/

4. Gaga, M., et al.: Lung nodules: a comprehensive review on current approach and management. Ann. Thoracic Med. 14(4), 226 (2019). https://doi.org/10.4103/atm.atm_110_19

5. He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770–778 (2016)

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