Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017
Medical Physics2018Vol. 45(10), pp. 4568–4581
Citations Over TimeTop 1% of 2018 papers
Jinzhong Yang, Harini Veeraraghavan, Samuel G. Armato, Keyvan Farahani, Justin Kirby, Jayashree Kalpathy‐Kramer, Wouter van Elmpt, André Dekker, Xiao Han, Xue Feng, Paul Aljabar, Bruno Oliveira, Brent van der Heyden, Leonid Zamdborg, Dao Lam, Mark J. Gooding, G Sharp
Abstract
The results of the challenge showed that the lungs and heart can be segmented fairly accurately by various algorithms, while deep-learning methods performed better on the esophagus. Our dataset together with the manual contours for all training cases continues to be available publicly as an ongoing benchmarking resource.
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