Early Experiences with Crowdsourcing Airway Annotations in Chest CT

Author:

Cheplygina Veronika,Perez-Rovira Adria,Kuo Wieying,Tiddens Harm A. W. M.,de Bruijne Marleen

Publisher

Springer International Publishing

Reference12 articles.

1. Albarqouni, S., Baur, C., Achilles, F., Belagiannis, V., Demirci, S., Navab, N.: AggNet: deep learning from crowds for mitosis detection in breast cancer histology images. IEEE Trans. Med. Imaging 35(5), 1313–1321 (2016)

2. Chen, J.J., Menezes, N.J., Bradley, A.D., North, T.A.: Opportunitiesfor crowdsourcing research on Amazon Mechanical Turk. In: CHI workshop on Crowdsourcing and Human Computation (2011)

3. Kuo, W., et al.: Assessment of bronchiectasis in children with cystic fibrosis by comparing airway and artery dimensions to normal controls on inspiratory and expiratory spirometer guided chest computed tomography. In: ECR 2015-European Congress of Radiology (2015)

4. Lo, P., Sporring, J., Ashraf, H., Pedersen, J.J., Bruijne, M.: Vessel-guided airway tree segmentation: a voxel classification approach. Med. Image Anal. 14(4), 527–538 (2010)

5. Maier-Hein, L., Kondermann, D., et al.: Crowdtruth validation: a new paradigm for validating algorithms that rely on image correspondences. Int. J. Comput. Assist. Radiol. Surg. 10(8), 1201–1212 (2015)

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