159 related articles for article (PubMed ID: 31886423)
1. Stability analysis of CT radiomic features with respect to segmentation variation in oropharyngeal cancer.
Liu R; Elhalawani H; Radwan Mohamed AS; Elgohari B; Court L; Zhu H; Fuller CD
Clin Transl Radiat Oncol; 2020 Mar; 21():11-18. PubMed ID: 31886423
[TBL] [Abstract][Full Text] [Related]
2. Reproducibility of F18-FDG PET radiomic features for different cervical tumor segmentation methods, gray-level discretization, and reconstruction algorithms.
Altazi BA; Zhang GG; Fernandez DC; Montejo ME; Hunt D; Werner J; Biagioli MC; Moros EG
J Appl Clin Med Phys; 2017 Nov; 18(6):32-48. PubMed ID: 28891217
[TBL] [Abstract][Full Text] [Related]
3. Reproducibility for Hepatocellular Carcinoma CT Radiomic Features: Influence of Delineation Variability Based on 3D-CT, 4D-CT and Multiple-Parameter MR Images.
Duan J; Qiu Q; Zhu J; Shang D; Dou X; Sun T; Yin Y; Meng X
Front Oncol; 2022; 12():881931. PubMed ID: 35494061
[TBL] [Abstract][Full Text] [Related]
4. Reproducibility and non-redundancy of radiomic features extracted from arterial phase CT scans in hepatocellular carcinoma patients: impact of tumor segmentation variability.
Qiu Q; Duan J; Duan Z; Meng X; Ma C; Zhu J; Lu J; Liu T; Yin Y
Quant Imaging Med Surg; 2019 Mar; 9(3):453-464. PubMed ID: 31032192
[TBL] [Abstract][Full Text] [Related]
5. Stability and reproducibility of computed tomography radiomic features extracted from peritumoral regions of lung cancer lesions.
Tunali I; Hall LO; Napel S; Cherezov D; Guvenis A; Gillies RJ; Schabath MB
Med Phys; 2019 Nov; 46(11):5075-5085. PubMed ID: 31494946
[TBL] [Abstract][Full Text] [Related]
6. Robustness of Radiomic Features: Two-Dimensional versus Three-Dimensional MRI-Based Feature Reproducibility in Lipomatous Soft-Tissue Tumors.
Sudjai N; Siriwanarangsun P; Lektrakul N; Saiviroonporn P; Maungsomboon S; Phimolsarnti R; Asavamongkolkul A; Chandhanayingyong C
Diagnostics (Basel); 2023 Jan; 13(2):. PubMed ID: 36673068
[TBL] [Abstract][Full Text] [Related]
7. Robust Radiomics feature quantification using semiautomatic volumetric segmentation.
Parmar C; Rios Velazquez E; Leijenaar R; Jermoumi M; Carvalho S; Mak RH; Mitra S; Shankar BU; Kikinis R; Haibe-Kains B; Lambin P; Aerts HJ
PLoS One; 2014; 9(7):e102107. PubMed ID: 25025374
[TBL] [Abstract][Full Text] [Related]
8. Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software.
Lee M; Woo B; Kuo MD; Jamshidi N; Kim JH
Korean J Radiol; 2017; 18(3):498-509. PubMed ID: 28458602
[TBL] [Abstract][Full Text] [Related]
9. Reliability of tumor segmentation in glioblastoma: Impact on the robustness of MRI-radiomic features.
Tixier F; Um H; Young RJ; Veeraraghavan H
Med Phys; 2019 Aug; 46(8):3582-3591. PubMed ID: 31131906
[TBL] [Abstract][Full Text] [Related]
10. Robustness of magnetic resonance imaging and positron emission tomography radiomic features in prostate cancer: Impact on recurrence prediction after radiation therapy.
Dutta A; Chan J; Haworth A; Dubowitz DJ; Kneebone A; Reynolds HM
Phys Imaging Radiat Oncol; 2024 Jan; 29():100530. PubMed ID: 38275002
[TBL] [Abstract][Full Text] [Related]
11. T2w-MRI signal normalization affects radiomics features reproducibility.
Scalco E; Belfatto A; Mastropietro A; Rancati T; Avuzzi B; Messina A; Valdagni R; Rizzo G
Med Phys; 2020 Apr; 47(4):1680-1691. PubMed ID: 31971614
[TBL] [Abstract][Full Text] [Related]
12. Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation.
Yamashita R; Perrin T; Chakraborty J; Chou JF; Horvat N; Koszalka MA; Midya A; Gonen M; Allen P; Jarnagin WR; Simpson AL; Do RKG
Eur Radiol; 2020 Jan; 30(1):195-205. PubMed ID: 31392481
[TBL] [Abstract][Full Text] [Related]
13. Interchangeability of radiomic features between [18F]-FDG PET/CT and [18F]-FDG PET/MR.
Vuong D; Tanadini-Lang S; Huellner MW; Veit-Haibach P; Unkelbach J; Andratschke N; Kraft J; Guckenberger M; Bogowicz M
Med Phys; 2019 Apr; 46(4):1677-1685. PubMed ID: 30714158
[TBL] [Abstract][Full Text] [Related]
14. Predicting the need for a replan in oropharyngeal cancer: A radiomic, clinical, and dosimetric model.
Chinnery TA; Lang P; Nichols AC; Mattonen SA
Med Phys; 2024 May; 51(5):3510-3520. PubMed ID: 38100260
[TBL] [Abstract][Full Text] [Related]
15. Uniqueness of radiomic features in non-small cell lung cancer.
Ge G; Zhang J
J Appl Clin Med Phys; 2022 Dec; 23(12):e13787. PubMed ID: 36173022
[TBL] [Abstract][Full Text] [Related]
16. Deep learning-based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study.
Chen H; Li S; Zhang Y; Liu L; Lv X; Yi Y; Ruan G; Ke C; Feng Y
Eur Radiol; 2022 Oct; 32(10):7248-7259. PubMed ID: 35420299
[TBL] [Abstract][Full Text] [Related]
17. Robustness of pulmonary nodule radiomic features on computed tomography as a function of varying radiation dose levels-a multi-dose in vivo patient study.
Bartholomeus GA; van Amsterdam WAC; Harder AMD; Willemink MJ; van Hamersvelt RW; de Jong PA; Leiner T
Eur Radiol; 2023 Oct; 33(10):7044-7055. PubMed ID: 37074424
[TBL] [Abstract][Full Text] [Related]
18. Deep Learning-based Image Conversion of CT Reconstruction Kernels Improves Radiomics Reproducibility for Pulmonary Nodules or Masses.
Choe J; Lee SM; Do KH; Lee G; Lee JG; Lee SM; Seo JB
Radiology; 2019 Aug; 292(2):365-373. PubMed ID: 31210613
[TBL] [Abstract][Full Text] [Related]
19. Robustness of Radiomics in Pre-Surgical Computer Tomography of Non-Small-Cell Lung Cancer.
Belfiore MP; Sansone M; Monti R; Marrone S; Fusco R; Nardone V; Grassi R; Reginelli A
J Pers Med; 2022 Dec; 13(1):. PubMed ID: 36675744
[TBL] [Abstract][Full Text] [Related]
20. Assessment of Stability and Discrimination Capacity of Radiomic Features on Apparent Diffusion Coefficient Images.
Bologna M; Corino VDA; Montin E; Messina A; Calareso G; Greco FG; Sdao S; Mainardi LT
J Digit Imaging; 2018 Dec; 31(6):879-894. PubMed ID: 29725965
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]