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Abstract
Linear scaling is used to convert raw computed tomography (CT) pixel values into Hounsfield units corresponding to different tissue values. Analysis of a benchmarking study, presented here, where the same CT scan was imported into and then exported from multiple radiotherapy treatment planning systems, found inconsistencies in HU scaling parameter values exported along with the images, particularly when images were exported using the Radiation Therapy Oncology Group format. Several methods of estimating conversion parameters, based on estimating pixel values corresponding to air and water within the image, for pelvic CT images from a large multi-centre trial were compared against original Digital Imaging and Communications in Medicine export parameters. In general using the mean of a sample region at the centroid of the bladder to estimate the value of water was more accurate than using the minimum or maximum or a single value at the centroid. Accuracy of methods of air estimation tested were dependent in part on features of the CT scanners and treatment planning systems, making it difficult to pick one method as superior that was independent of scanner and treatment planning system type. Based on the above analysis, methods for estimating air and water were selected for use in performing linear scaling of a set of pelvic CT images prior to their use in an interpatient image registration application. The selected methods were validated against a more recent and homogeneous dataset. Estimation error was found to be much lower within the validation set.
Original language | English |
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Pages (from-to) | 739-745 |
Number of pages | 7 |
Journal | Australasian Physical and Engineering Sciences in Medicine |
Volume | 41 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Sep 2018 |
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Dive into the research topics of 'Estimation of Hounsfield unit conversion parameters for pelvic CT images'. Together they form a unique fingerprint.Projects
- 1 Finished
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Radiotherapy treatment for prostate cancer - a change in practice based on direct evidence for targeting and toxicity effects using real outcomes data
Ebert, M., Dowling, J., Denham, J., Joseph, D., Gulliford, S., Dearnaley, D., Haworth, A., Holloway, L., Kron, T. & Greer, P.
National Health & Medical Research Council NHMRC
1/01/15 → 31/12/19
Project: Research