245 related articles for article (PubMed ID: 31609076)
1. Technical Note: Proof of concept for radiomics-based quality assurance for computed tomography.
Branco LRF; Ger RB; Mackin DS; Zhou S; Court LE; Layman RR
J Appl Clin Med Phys; 2019 Nov; 20(11):199-205. PubMed ID: 31609076
[TBL] [Abstract][Full Text] [Related]
2. The impact of phantom design and material-dependence on repeatability and reproducibility of CT-based radiomics features.
Li Y; Reyhan M; Zhang Y; Wang X; Zhou J; Zhang Y; Yue NJ; Nie K
Med Phys; 2022 Mar; 49(3):1648-1659. PubMed ID: 35103332
[TBL] [Abstract][Full Text] [Related]
3. Time stability of delta-radiomics features and the impact on patient analysis in longitudinal CT images.
Plautz TE; Zheng C; Noid G; Li XA
Med Phys; 2019 Apr; 46(4):1663-1676. PubMed ID: 30695103
[TBL] [Abstract][Full Text] [Related]
4. Measuring Computed Tomography Scanner Variability of Radiomics Features.
Mackin D; Fave X; Zhang L; Fried D; Yang J; Taylor B; Rodriguez-Rivera E; Dodge C; Jones AK; Court L
Invest Radiol; 2015 Nov; 50(11):757-65. PubMed ID: 26115366
[TBL] [Abstract][Full Text] [Related]
5. Intrinsic dependencies of CT radiomic features on voxel size and number of gray levels.
Shafiq-Ul-Hassan M; Zhang GG; Latifi K; Ullah G; Hunt DC; Balagurunathan Y; Abdalah MA; Schabath MB; Goldgof DG; Mackin D; Court LE; Gillies RJ; Moros EG
Med Phys; 2017 Mar; 44(3):1050-1062. PubMed ID: 28112418
[TBL] [Abstract][Full Text] [Related]
6. Statistical Analysis on Impact of Image Preprocessing of CT Texture Patterns and Its CT Radiomic Feature Stability: A Phantom Study.
Palani D; Ganesh KM; Karunagaran L; Govindaraj K; Shanmugam S
Asian Pac J Cancer Prev; 2023 Jun; 24(6):2061-2072. PubMed ID: 37378937
[TBL] [Abstract][Full Text] [Related]
7. Precision of quantitative computed tomography texture analysis using image filtering: A phantom study for scanner variability.
Yasaka K; Akai H; Mackin D; Court L; Moros E; Ohtomo K; Kiryu S
Medicine (Baltimore); 2017 May; 96(21):e6993. PubMed ID: 28538408
[TBL] [Abstract][Full Text] [Related]
8. Quantitation of clinical feedback on image quality differences between two CT scanner models.
Bache ST; Stauduhar PJ; Liu X; Loyer EM; John RX
J Appl Clin Med Phys; 2017 Mar; 18(2):163-169. PubMed ID: 28300384
[TBL] [Abstract][Full Text] [Related]
9. Performance evaluation of an 85-cm-bore X-ray computed tomography scanner designed for radiation oncology and comparison with current diagnostic CT scanners.
Garcia-Ramirez JL; Mutic S; Dempsey JF; Low DA; Purdy JA
Int J Radiat Oncol Biol Phys; 2002 Mar; 52(4):1123-31. PubMed ID: 11958910
[TBL] [Abstract][Full Text] [Related]
10. 100 days with scans of the same Catphan phantom on the same CT scanner.
Husby E; Svendsen ED; Andersen HK; Martinsen ACT
J Appl Clin Med Phys; 2017 Nov; 18(6):224-231. PubMed ID: 28921910
[TBL] [Abstract][Full Text] [Related]
11. A quality assurance framework for the fully automated and objective evaluation of image quality in cone-beam computed tomography.
Steiding C; Kolditz D; Kalender WA
Med Phys; 2014 Mar; 41(3):031901. PubMed ID: 24593719
[TBL] [Abstract][Full Text] [Related]
12. Quantification and homogenization of image noise between two CT scanner models.
Einstein SA; Rong XJ; Jensen CT; Liu X
J Appl Clin Med Phys; 2020 Jan; 21(1):174-178. PubMed ID: 31859454
[TBL] [Abstract][Full Text] [Related]
13. A routine quality assurance test for CT automatic exposure control systems.
Iball GR; Moore AC; Crawford EJ
J Appl Clin Med Phys; 2016 Jul; 17(4):291-306. PubMed ID: 27455490
[TBL] [Abstract][Full Text] [Related]
14. Validation of A Method to Compensate Multicenter Effects Affecting CT Radiomics.
Orlhac F; Frouin F; Nioche C; Ayache N; Buvat I
Radiology; 2019 Apr; 291(1):53-59. PubMed ID: 30694160
[TBL] [Abstract][Full Text] [Related]
15. Reliability of CT-based texture features: Phantom study.
Varghese BA; Hwang D; Cen SY; Levy J; Liu D; Lau C; Rivas M; Desai B; Goodenough DJ; Duddalwar VA
J Appl Clin Med Phys; 2019 Aug; 20(8):155-163. PubMed ID: 31222919
[TBL] [Abstract][Full Text] [Related]
16. Discriminative feature representation: an effective postprocessing solution to low dose CT imaging.
Chen Y; Liu J; Hu Y; Yang J; Shi L; Shu H; Gui Z; Coatrieux G; Luo L
Phys Med Biol; 2017 Mar; 62(6):2103-2131. PubMed ID: 28212114
[TBL] [Abstract][Full Text] [Related]
17. Evaluation of commercial extension plates for the ACR CT accreditation phantom.
Greene-Donnelly KA; Ogden KM
J Appl Clin Med Phys; 2016 Jan; 17(1):416-420. PubMed ID: 26894348
[TBL] [Abstract][Full Text] [Related]
18. Effects of alterations in positron emission tomography imaging parameters on radiomics features.
Ger RB; Meier JG; Pahlka RB; Gay S; Mumme R; Fuller CD; Li H; Howell RM; Layman RR; Stafford RJ; Zhou S; Mawlawi O; Court LE
PLoS One; 2019; 14(9):e0221877. PubMed ID: 31487307
[TBL] [Abstract][Full Text] [Related]
19. The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers.
Zhang X; Iqbal Bin Saripan M; Wu Y; Wang Z; Wen D; Cao Z; Wang B; Xu S; Liu Y; Marhaban MH; Dong X
BMC Med Imaging; 2024 Jun; 24(1):137. PubMed ID: 38844854
[TBL] [Abstract][Full Text] [Related]
20. Technical Note: Evaluation of a 160-mm/256-row CT scanner for whole-heart quantitative myocardial perfusion imaging.
So A; Imai Y; Nett B; Jackson J; Nett L; Hsieh J; Wisenberg G; Teefy P; Yadegari A; Islam A; Lee TY
Med Phys; 2016 Aug; 43(8):4821. PubMed ID: 27487900
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
