Harnessing uncertainty in radiotherapy auto-segmentation quality assurance

Author:

Wahid Kareem A.ORCID,Sahlsten JaakkoORCID,Jaskari JoelORCID,Dohopolski Michael J.ORCID,Kaski KimmoORCID,He Renjie,Glerean EnricoORCID,Kann Benjamin H.ORCID,Mäkitie AnttiORCID,Fuller Clifton D.,Naser Mohamed A.ORCID,Fuentes David

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,Radiation

Reference23 articles.

1. A network score-based metric to optimize the quality assurance of automatic radiotherapy target segmentations;Rodríguez Outeiral;Phys Imaging Radiat Oncol,2023

2. Guo C, Pleiss G, Sun Y, Weinberger KQ. On calibration of modern neural networks. In: Precup D, Teh YW, editors. Proceedings of the 34th international conference on machine learning, vol. 70, PMLR; 06--11 Aug 2017, p. 1321–30.

3. Revisiting softmax for uncertainty approximation in text classification;Holm;Information,2023

4. Pearce T, Brintrup A, Zhu J. Understanding softmax confidence and uncertainty. arXiv [csLG] 2021.

5. Uncertainty-aware deep learning methods for robust diabetic retinopathy classification;Jaskari;IEEE Access,2022

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