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Connection

Samuel Armato to Lung Neoplasms

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This is a "connection" page, showing publications Samuel Armato has written about Lung Neoplasms.
Samuel Armato
Connection Strength
4.995
Lung Neoplasms
  1. 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: 0.318
  2. Imaging in pleural mesothelioma: A review of the 15th International Conference of the International Mesothelioma Interest Group. Lung Cancer. 2022 02; 164:76-83.
    View in: PubMed
    Score: 0.296
  3. Deep Learning Demonstrates Potential for Lung Cancer Detection in Chest Radiography. Radiology. 2020 12; 297(3):697-698.
    View in: PubMed
    Score: 0.272
  4. Response. Chest. 2019 10; 156(4):810-811.
    View in: PubMed
    Score: 0.254
  5. Accuracy of the Vancouver Lung Cancer Risk Prediction Model Compared With That of Radiologists. Chest. 2019 07; 156(1):112-119.
    View in: PubMed
    Score: 0.246
  6. Correlation of patient survival with clinical tumor measurements in malignant pleural mesothelioma. Eur Radiol. 2019 Jun; 29(6):2981-2988.
    View in: PubMed
    Score: 0.241
  7. Revised Modified Response Evaluation Criteria in Solid Tumors for Assessment of Response in Malignant Pleural Mesothelioma (Version 1.1). J Thorac Oncol. 2018 07; 13(7):1012-1021.
    View in: PubMed
    Score: 0.231
  8. Imaging in pleural mesothelioma: A review of the 13th International Conference of the International Mesothelioma Interest Group. Lung Cancer. 2016 11; 101:48-58.
    View in: PubMed
    Score: 0.205
  9. Toward Understanding the Size Dependence of Shape Features for Predicting Spiculation in Lung Nodules for Computer-Aided Diagnosis. J Digit Imaging. 2015 Dec; 28(6):704-17.
    View in: PubMed
    Score: 0.195
  10. 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: 0.195
  11. 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: 0.190
  12. Imaging in pleural mesothelioma: a review of the 11th International Conference of the International Mesothelioma Interest Group. Lung Cancer. 2013 Nov; 82(2):190-6.
    View in: PubMed
    Score: 0.166
  13. Variability of tumor area measurements for response assessment in malignant pleural mesothelioma. Med Phys. 2013 Aug; 40(8):081916.
    View in: PubMed
    Score: 0.166
  14. Disease volumes as a marker for patient response in malignant pleural mesothelioma. Ann Oncol. 2013 Apr; 24(4):999-1005.
    View in: PubMed
    Score: 0.158
  15. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans. Med Phys. 2011 Feb; 38(2):915-31.
    View in: PubMed
    Score: 0.139
  16. Assessment of radiologist performance in the detection of lung nodules: dependence on the definition of "truth". Acad Radiol. 2009 Jan; 16(1):28-38.
    View in: PubMed
    Score: 0.121
  17. The Reference Image Database to Evaluate Response to therapy in lung cancer (RIDER) project: a resource for the development of change-analysis software. Clin Pharmacol Ther. 2008 Oct; 84(4):448-56.
    View in: PubMed
    Score: 0.119
  18. Discrete-space versus continuous-space lesion boundary and area definitions. Med Phys. 2008 Sep; 35(9):4070-8.
    View in: PubMed
    Score: 0.118
  19. The Lung Image Database Consortium (LIDC): ensuring the integrity of expert-defined "truth". Acad Radiol. 2007 Dec; 14(12):1455-63.
    View in: PubMed
    Score: 0.112
  20. Evaluation of automated lung nodule detection on low-dose computed tomography scans from a lung cancer screening program(1). Acad Radiol. 2005 Mar; 12(3):337-46.
    View in: PubMed
    Score: 0.092
  21. Imaging in pleural Mesothelioma: A review of the 16th International Conference of the International Mesothelioma Interest Group. Lung Cancer. 2024 Jul; 193:107832.
    View in: PubMed
    Score: 0.088
  22. Emphysema Detection in the Course of Lung Cancer Screening: Optimizing a Rare Opportunity to Impact Population Health. Ann Am Thorac Soc. 2023 04; 20(4):499-503.
    View in: PubMed
    Score: 0.081
  23. Automated detection of lung nodules in CT scans: preliminary results. Med Phys. 2001 Aug; 28(8):1552-61.
    View in: PubMed
    Score: 0.072
  24. Optimization of response classification criteria for patients with malignant pleural mesothelioma, a validation study. Lung Cancer. 2019 12; 138:139-140.
    View in: PubMed
    Score: 0.064
  25. EURACAN/IASLC Proposals for Updating the Histologic Classification of Pleural Mesothelioma: Towards a More Multidisciplinary Approach. J Thorac Oncol. 2020 01; 15(1):29-49.
    View in: PubMed
    Score: 0.063
  26. Radiologic Considerations and Standardization of Malignant Pleural Mesothelioma Imaging Within Clinical Trials: Consensus Statement from the NCI Thoracic Malignancy Steering Committee - International Association for the Study of Lung Cancer - Mesothelioma Applied Research Foundation Clinical Trials Planning Meeting. J Thorac Oncol. 2019 10; 14(10):1718-1731.
    View in: PubMed
    Score: 0.063
  27. Treatment of Malignant Pleural Mesothelioma: American Society of Clinical Oncology Clinical Practice Guideline. J Clin Oncol. 2018 05 01; 36(13):1343-1373.
    View in: PubMed
    Score: 0.056
  28. Quality assurance and quantitative imaging biomarkers in low-dose CT lung cancer screening. Br J Radiol. 2018 Oct; 91(1090):20170401.
    View in: PubMed
    Score: 0.056
  29. Clinical significance of noncalcified lung nodules in patients with breast cancer. Breast Cancer Res Treat. 2016 Sep; 159(2):265-71.
    View in: PubMed
    Score: 0.051
  30. 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: 0.050
  31. Role of the Quantitative Imaging Biomarker Alliance in optimizing CT for the evaluation of lung cancer screen-detected nodules. J Am Coll Radiol. 2015 Apr; 12(4):390-5.
    View in: PubMed
    Score: 0.046
  32. Computer-aided nodule detection system: results in an unselected series of consecutive chest radiographs. Acad Radiol. 2015 Apr; 22(4):475-80.
    View in: PubMed
    Score: 0.046
  33. 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: 0.045
  34. Three-dimensional stereoscopic volume rendering of malignant pleural mesothelioma. Int Surg. 2012 Jan-Mar; 97(1):65-70.
    View in: PubMed
    Score: 0.037
  35. Lymphatic vessel density is not associated with lymph node metastasis in non-small cell lung carcinoma. Arch Pathol Lab Med. 2008 Dec; 132(12):1882-8.
    View in: PubMed
    Score: 0.030
  36. The Lung Image Database Consortium (LIDC) data collection process for nodule detection and annotation. Acad Radiol. 2007 Dec; 14(12):1464-74.
    View in: PubMed
    Score: 0.028
  37. The Lung Image Database Consortium (LIDC): a comparison of different size metrics for pulmonary nodule measurements. Acad Radiol. 2007 Dec; 14(12):1475-85.
    View in: PubMed
    Score: 0.028
  38. The Lung Image Database Consortium (LIDC): an evaluation of radiologist variability in the identification of lung nodules on CT scans. Acad Radiol. 2007 Nov; 14(11):1409-21.
    View in: PubMed
    Score: 0.028
  39. Temporal subtraction of dual-energy chest radiographs. Med Phys. 2006 Jun; 33(6):1911-9.
    View in: PubMed
    Score: 0.025
  40. Automated detection of lung nodules in CT scans: false-positive reduction with the radial-gradient index. Med Phys. 2006 Apr; 33(4):1133-40.
    View in: PubMed
    Score: 0.025
  41. Modeling of mesothelioma growth demonstrates weaknesses of current response criteria. Lung Cancer. 2006 May; 52(2):141-8.
    View in: PubMed
    Score: 0.025
  42. Automated lung segmentation for thoracic CT impact on computer-aided diagnosis. Acad Radiol. 2004 Sep; 11(9):1011-21.
    View in: PubMed
    Score: 0.022
  43. Assessment methodologies and statistical issues for computer-aided diagnosis of lung nodules in computed tomography: contemporary research topics relevant to the lung image database consortium. Acad Radiol. 2004 Apr; 11(4):462-75.
    View in: PubMed
    Score: 0.022
  44. Automated lung nodule classification following automated nodule detection on CT: a serial approach. Med Phys. 2003 Jun; 30(6):1188-97.
    View in: PubMed
    Score: 0.020
  45. Automated detection of lung nodules in CT scans: effect of image reconstruction algorithm. Med Phys. 2003 Mar; 30(3):461-72.
    View in: PubMed
    Score: 0.020
  46. Lung cancers missed at low-dose helical CT screening in a general population: comparison of clinical, histopathologic, and imaging findings. Radiology. 2002 Dec; 225(3):673-83.
    View in: PubMed
    Score: 0.020
  47. Lung cancer: performance of automated lung nodule detection applied to cancers missed in a CT screening program. Radiology. 2002 Dec; 225(3):685-92.
    View in: PubMed
    Score: 0.020
  48. Computer-aided diagnosis in medical imaging. IEEE Trans Med Imaging. 2001 Dec; 20(12):1205-8.
    View in: PubMed
    Score: 0.018
  49. Evaluation of lung MDCT nodule annotation across radiologists and methods. Acad Radiol. 2006 Oct; 13(10):1254-65.
    View in: PubMed
    Score: 0.006
  50. Vessel tree reconstruction in thoracic CT scans with application to nodule detection. IEEE Trans Med Imaging. 2005 Apr; 24(4):486-99.
    View in: PubMed
    Score: 0.006
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.