https://novaprd-lb.newcastle.edu.au/vital/access/manager/Index en-au 5 A deep learning model to generate synthetic CT for prostate MR-only radiotherapy dose planning: a multicenter study https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:53856 Wed 28 Feb 2024 15:05:06 AEDT ]]> Quality assurance for MRI-only radiation therapy: A voxel-wise population-based methodology for image and dose assessment of synthetic CT generation methods https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:52863 Mon 30 Oct 2023 10:01:55 AEDT ]]> Comparison of deep learning-based and patch-based methods for pseudo-CT generation in MRI-based prostate dose planning https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:46578 2-weighted MRIs were acquired in addition to planning CTs. The pCTs were generated from the MRIs using 7 configurations: 4 GANs (L2, single-scale PL, multiscale PL, weighted multiscale PL), 2 U-Net (L2 and single-scale PL), and the PBM. The imaging endpoints were mean absolute error and mean error, in Hounsfield units, between the reference CT (CTref) and the pCT. Dose uncertainties were quantified as mean absolute differences between the dose volume histograms (DVHs) calculated from the CTref and pCT obtained by each method. Three-dimensional gamma indexes were analyzed. Results: Considering the image uncertainties in the whole pelvis, GAN L2 and U-Net L2 showed the lowest mean absolute error (≤34.4 Hounsfield units). The mean errors were not different than 0 (P ≤ .05). The PBM provided the highest uncertainties. Very few DVH points differed when comparing GAN L2 or U-Net L2 DVHs and CTref DVHs (P ≤ .05). Their dose uncertainties were ≤0.6% for the prostate planning target Volume V95%, ≤0.5% for the rectum V70Gy, and ≤0.1% for the bladder V50Gy. The PBM, U-Net PL, and GAN PL presented the highest systematic dose uncertainties. The gamma pass rates were >99% for all DLMs. The mean calculation time to generate 1 pCT was 15 s for the DLMs and 62 min for the PBM. Conclusions: Generating pCT for MRI dose planning with DLMs and PBM provided low-dose uncertainties. In particular, the GAN L2 and U-Net L2 provided the lowest dose uncertainties together with a low computation time]]> Mon 28 Nov 2022 16:01:26 AEDT ]]> Voxel-wise analysis for spatial characterisation of pseudo-ct errors in MRI-only radiotherapy planning https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:43841 Mon 20 Nov 2023 14:35:06 AEDT ]]> Image synthesis for MRI-only radiotherapy treatment planning https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:46392 Fri 25 Nov 2022 13:59:19 AEDT ]]> Pseudo-CT generation by conditional inference random forest for MRI-based radiotherapy treatment planning https://novaprd-lb.newcastle.edu.au/vital/access/manager/Repository/uon:32135 Fri 04 May 2018 15:36:57 AEST ]]>