Correction: Innovative approaches in precision radiation oncology: advanced imaging technologies and challenges which shape the future of radiation therapy

The reference in the caption of Figure 6 was erroneously cited as Maas et al. (104). It should be Ronneberger et al. (59).

The caption of Figure 6 has been updated to “Architecture of the U-Net. Reproduced with permission from Ronneberger et al. (59).”

The reference in the caption of Figure 9 was erroneously cited as Alexander et al. (227).

It should be Wang et al. (224).

The sentence “Reprinted from Alexander et al. (227).” has been corrected to “Reproduced with permission from Wang et al. (224).” in the caption of Figure 9.

Reference 224 was erroneously written as “Wang S, Chen Y, Jarvis LA, Tang Y, Gladstone DJ, Samkoe KS, et al. Robust Real-time segmentation of bio-morphological features in Human Cherenkov imaging during radiotherapy via deep learning. arXiv [Preprint]. arXiv:2409.05666v1 (2014). doi: 10.1002/mp.18002”. It should be “Wang S, Chen Y, Jarvis LA, Tang Y, Gladstone DJ, Samkoe KS, et al. Robust real-time segmentation of bio-morphological features in human Cherenkov imaging during radiotherapy via deep learning. Med Phys. (2025) 52:e18002. doi: 10.1002/mp.18002.”

Reference 1 was incorrectly cited in section 6 Image synthesis in RT, 6.1 Deep learning networks in medical images, Paragraph 2. Reference 59 should have been cited.

The sentence previously read: “One of the most well-known CNN models is the U-shaped net (U-Net) proposed by Ronneberger et al. (1) (Figure 6).”

The sentence now reads: “One of the most well-known CNN models is the U-shaped net (U-Net) proposed by Ronneberger et al. (59) (Figure 6).”

The original version of this article has been updated.

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