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Connection

Co-Authors

This is a "connection" page, showing publications co-authored by Samuel G. Armato and Christopher M Straus.
Connection Strength

2.315
  1. Convolutional Neural Networks for Segmentation of Malignant Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance). ArXiv. 2023 Nov 30.
    View in: PubMed
    Score: 0.243
  2. Considerations for Imaging of Malignant Pleural Mesothelioma: A Consensus Statement from the International Mesothelioma Interest Group. J Thorac Oncol. 2023 03; 18(3):278-298.
    View in: PubMed
    Score: 0.228
  3. The role of imaging in diagnosis and management of malignant peritoneal mesothelioma: a systematic review. Abdom Radiol (NY). 2022 05; 47(5):1725-1740.
    View in: PubMed
    Score: 0.216
  4. Deep learning-based segmentation of malignant pleural mesothelioma tumor on computed tomography scans: application to scans demonstrating pleural effusion. J Med Imaging (Bellingham). 2020 Jan; 7(1):012705.
    View in: PubMed
    Score: 0.187
  5. Correlation of patient survival with clinical tumor measurements in malignant pleural mesothelioma. Eur Radiol. 2019 Jun; 29(6):2981-2988.
    View in: PubMed
    Score: 0.173
  6. Deep convolutional neural networks for the automated segmentation of malignant pleural mesothelioma on computed tomography scans. J Med Imaging (Bellingham). 2018 Jul; 5(3):034503.
    View in: PubMed
    Score: 0.170
  7. Comparison of Two Deformable Registration Algorithms in the Presence of Radiologic Change Between Serial Lung CT Scans. J Digit Imaging. 2015 Dec; 28(6):755-60.
    View in: PubMed
    Score: 0.140
  8. Imaging in pleural mesothelioma: A review of the 12th International Conference of the International Mesothelioma Interest Group. Lung Cancer. 2015 Nov; 90(2):148-54.
    View in: PubMed
    Score: 0.136
  9. Radiologic-pathologic correlation of mesothelioma tumor volume. Lung Cancer. 2015 Mar; 87(3):278-82.
    View in: PubMed
    Score: 0.132
  10. Variability of tumor area measurements for response assessment in malignant pleural mesothelioma. Med Phys. 2013 Aug; 40(8):081916.
    View in: PubMed
    Score: 0.119
  11. Disease volumes as a marker for patient response in malignant pleural mesothelioma. Ann Oncol. 2013 Apr; 24(4):999-1005.
    View in: PubMed
    Score: 0.113
  12. Lung texture in serial thoracic CT scans: assessment of change introduced by image registration. Med Phys. 2012 Aug; 39(8):4679-90.
    View in: PubMed
    Score: 0.111
  13. Characterization of mesothelioma and tissues present in contrast-enhanced thoracic CT scans. Med Phys. 2011 Feb; 38(2):942-7.
    View in: PubMed
    Score: 0.100
  14. The influence of initial outlines on manual segmentation. Med Phys. 2010 May; 37(5):2153-8.
    View in: PubMed
    Score: 0.095
  15. North American Multicenter Volumetric CT Study for Clinical Staging of Malignant Pleural Mesothelioma: Feasibility and Logistics of Setting Up a Quantitative Imaging Study. J Thorac Oncol. 2016 08; 11(8):1335-1344.
    View in: PubMed
    Score: 0.036
  16. Lung texture in serial thoracic CT scans: correlation with radiologist-defined severity of acute changes following radiation therapy. Phys Med Biol. 2014 Sep 21; 59(18):5387-98.
    View in: PubMed
    Score: 0.032
  17. CT-based pulmonary artery measurements for the assessment of pulmonary hypertension. Acad Radiol. 2014 Apr; 21(4):523-30.
    View in: PubMed
    Score: 0.031
  18. Lung volume measurements as a surrogate marker for patient response in malignant pleural mesothelioma. J Thorac Oncol. 2013 Apr; 8(4):478-86.
    View in: PubMed
    Score: 0.029
  19. Computerized segmentation and measurement of malignant pleural mesothelioma. Med Phys. 2011 Jan; 38(1):238-44.
    View in: PubMed
    Score: 0.025
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.