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. 2022 Jul 18;12(7):e059000. doi: 10.1136/bmjopen-2021-059000

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© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Comparison of the expert segmentation (reference) and the three-dimensional (3D) dual-path CNN tumour core segmentation in the in-house data for high-grade glioma (HGG) and meningioma (MNG) cases overlaid on contrast enhanced T1 weighted. Voxels misclassified by the 3D dual-path CNN are visible in HGG cases #07 and #12 (top and middle row). The 3D dual-path CNN failed to correctly outline the tumour and included normal brain structures in the left medial temporal lobe for MNG case #04 (bottom row). CNN, convolutional neural network.