Connection

Co-Authors

This is a "connection" page, showing publications co-authored by LAURENCE EDWARD COURT and DENNIS STEPHEN MACKIN.
Connection Strength

4.248
  1. Matching and Homogenizing Convolution Kernels for Quantitative Studies in Computed Tomography. Invest Radiol. 2019 05; 54(5):288-295.
    View in: PubMed
    Score: 0.681
  2. Effect of tube current on computed tomography radiomic features. Sci Rep. 2018 02 05; 8(1):2354.
    View in: PubMed
    Score: 0.625
  3. Correction: Harmonizing the pixel size in retrospective computed tomography radiomics studies. PLoS One. 2018; 13(1):e0191597.
    View in: PubMed
    Score: 0.623
  4. Harmonizing the pixel size in retrospective computed tomography radiomics studies. PLoS One. 2017; 12(9):e0178524.
    View in: PubMed
    Score: 0.609
  5. Radiomics feature robustness as measured using an MRI phantom. Sci Rep. 2021 02 17; 11(1):3973.
    View in: PubMed
    Score: 0.193
  6. Radiomics features of the primary tumor fail to improve prediction of overall survival in large cohorts of CT- and PET-imaged head and neck cancer patients. PLoS One. 2019; 14(9):e0222509.
    View in: PubMed
    Score: 0.175
  7. Practical guidelines for handling head and neck computed tomography artifacts for quantitative image analysis. Comput Med Imaging Graph. 2018 11; 69:134-139.
    View in: PubMed
    Score: 0.163
  8. Comprehensive Investigation on Controlling for CT Imaging Variabilities in Radiomics Studies. Sci Rep. 2018 08 29; 8(1):13047.
    View in: PubMed
    Score: 0.163
  9. Guidelines and Experience Using Imaging Biomarker Explorer (IBEX) for Radiomics. J Vis Exp. 2018 01 08; (131).
    View in: PubMed
    Score: 0.156
  10. Delta-radiomics features for the prediction of patient outcomes in non-small cell lung cancer. Sci Rep. 2017 04 03; 7(1):588.
    View in: PubMed
    Score: 0.147
  11. Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer? Med Phys. 2015 Dec; 42(12):6784-97.
    View in: PubMed
    Score: 0.134
  12. Measuring Computed Tomography Scanner Variability of Radiomics Features. Invest Radiol. 2015 Nov; 50(11):757-65.
    View in: PubMed
    Score: 0.134
  13. Computed Tomography Radiomics Kinetics as Early Imaging Correlates of Osteoradionecrosis in Oropharyngeal Cancer Patients. Front Artif Intell. 2021; 4:618469.
    View in: PubMed
    Score: 0.049
  14. Technical Note: Proof of concept for radiomics-based quality assurance for computed tomography. J Appl Clin Med Phys. 2019 Nov; 20(11):199-205.
    View in: PubMed
    Score: 0.044
  15. Imaging-Genomic Study of Head and Neck Squamous Cell Carcinoma: Associations Between Radiomic Phenotypes and Genomic Mechanisms via Integration of The Cancer Genome Atlas and The Cancer Imaging Archive. JCO Clin Cancer Inform. 2019 02; 3:1-9.
    View in: PubMed
    Score: 0.042
  16. Lung tumor segmentation methods: Impact on the uncertainty of radiomics features for non-small cell lung cancer. PLoS One. 2018; 13(10):e0205003.
    View in: PubMed
    Score: 0.041
  17. Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges. Front Oncol. 2018; 8:294.
    View in: PubMed
    Score: 0.041
  18. Correction to: A predictive model for distinguishing radiation necrosis from tumour progression after gamma knife radiosurgery based on radiomic features from MR images. Eur Radiol. 2018 08; 28(8):3570-3571.
    View in: PubMed
    Score: 0.040
  19. Prognostic value of combining a quantitative image feature from positron emission tomography with clinical factors in oligometastatic non-small cell lung cancer. Radiother Oncol. 2018 02; 126(2):362-367.
    View in: PubMed
    Score: 0.039
  20. A predictive model for distinguishing radiation necrosis from tumour progression after gamma knife radiosurgery based on radiomic features from MR images. Eur Radiol. 2018 Jun; 28(6):2255-2263.
    View in: PubMed
    Score: 0.039
  21. Cost-effective immobilization for whole brain radiation therapy. J Appl Clin Med Phys. 2017 Jul; 18(4):116-122.
    View in: PubMed
    Score: 0.037
  22. Precision of quantitative computed tomography texture analysis using image filtering: A phantom study for scanner variability. Medicine (Baltimore). 2017 May; 96(21):e6993.
    View in: PubMed
    Score: 0.037
  23. Intrinsic dependencies of CT radiomic features on voxel size and number of gray levels. Med Phys. 2017 Mar; 44(3):1050-1062.
    View in: PubMed
    Score: 0.037
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.