| Autor: |
Dennis Mackin, Xenia Fave, Lifei Zhang, Jinzhong Yang, A Kyle Jones, Chaan S Ng, Laurence Court |
| Jazyk: |
angličtina |
| Rok vydání: |
2017 |
| Předmět: |
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| Zdroj: |
PLoS ONE, Vol 12, Iss 9, p e0178524 (2017) |
| Druh dokumentu: |
article |
| ISSN: |
1932-6203 |
| DOI: |
10.1371/journal.pone.0178524 |
| Popis: |
Consistent pixel sizes are of fundamental importance for assessing texture features that relate intensity and spatial information in radiomics studies. To correct for the effects of variable pixel sizes, we combined image resampling with Butterworth filtering in the frequency domain and tested the correction on computed tomography (CT) scans of lung cancer patients reconstructed 5 times with pixel sizes varying from 0.59 to 0.98 mm. One hundred fifty radiomics features were calculated for each preprocessing and field-of-view combination. Intra-patient agreement and inter-patient agreement were compared using the overall concordance correlation coefficient (OCCC). To further evaluate the corrections, hierarchical clustering was used to identify patient scans before and after correction. To assess the general applicability of the corrections, they were applied to 17 CT scans of a radiomics phantom. The reduction in the inter-scanner variability relative to non-small cell lung cancer patient scans was quantified. The variation in pixel sizes caused the intra-patient variability to be large (OCCC |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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