The University of Chicago Header Logo

Connection

Co-Authors

This is a "connection" page, showing publications co-authored by Feng Li and Kunio Doi.
Connection Strength

3.923
  1. Improved detection of subtle lung nodules by use of chest radiographs with bone suppression imaging: receiver operating characteristic analysis with and without localization. AJR Am J Roentgenol. 2011 May; 196(5):W535-41.
    View in: PubMed
    Score: 0.402
  2. Subjective similarity of patterns of diffuse interstitial lung disease on thin-section CT: an observer performance study. Acad Radiol. 2009 Apr; 16(4):477-85.
    View in: PubMed
    Score: 0.348
  3. Improving radiologists' recommendations with computer-aided diagnosis for management of small nodules detected by CT. Acad Radiol. 2006 Aug; 13(8):943-50.
    View in: PubMed
    Score: 0.289
  4. Computer-aided detection of peripheral lung cancers missed at CT: ROC analyses without and with localization. Radiology. 2005 Nov; 237(2):684-90.
    View in: PubMed
    Score: 0.275
  5. Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy. AJR Am J Roentgenol. 2004 Nov; 183(5):1209-15.
    View in: PubMed
    Score: 0.256
  6. Malignant versus benign nodules at CT screening for lung cancer: comparison of thin-section CT findings. Radiology. 2004 Dec; 233(3):793-8.
    View in: PubMed
    Score: 0.256
  7. Low-dose computed tomography screening for lung cancer in a general population: characteristics of cancer in non-smokers versus smokers. Acad Radiol. 2003 Sep; 10(9):1013-20.
    View in: PubMed
    Score: 0.236
  8. 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: 0.224
  9. Small lung cancers: improved detection by use of bone suppression imaging--comparison with dual-energy subtraction chest radiography. Radiology. 2011 Dec; 261(3):937-49.
    View in: PubMed
    Score: 0.103
  10. Quantitative evaluation of liver function with use of gadoxetate disodium-enhanced MR imaging. Radiology. 2011 Sep; 260(3):727-33.
    View in: PubMed
    Score: 0.102
  11. True detection versus "accidental" detection of small lung cancer by a computer-aided detection (CAD) program on chest radiographs. J Digit Imaging. 2010 Feb; 23(1):66-72.
    View in: PubMed
    Score: 0.088
  12. Usefulness of computer-aided diagnosis schemes for vertebral fractures and lung nodules on chest radiographs. AJR Am J Roentgenol. 2008 Jul; 191(1):260-5.
    View in: PubMed
    Score: 0.083
  13. An investigation of radiologists' perception of lesion similarity: observations with paired breast masses on mammograms and paired lung nodules on CT images. Acad Radiol. 2008 Jul; 15(7):887-94.
    View in: PubMed
    Score: 0.083
  14. Improved detection of small lung cancers with dual-energy subtraction chest radiography. AJR Am J Roentgenol. 2008 Apr; 190(4):886-91.
    View in: PubMed
    Score: 0.081
  15. Computerized detection of lung nodules in thin-section CT images by use of selective enhancement filters and an automated rule-based classifier. Acad Radiol. 2008 Feb; 15(2):165-75.
    View in: PubMed
    Score: 0.080
  16. Lung cancers missed on chest radiographs: results obtained with a commercial computer-aided detection program. Radiology. 2008 Jan; 246(1):273-80.
    View in: PubMed
    Score: 0.080
  17. Computer-aided diagnosis for improved detection of lung nodules by use of posterior-anterior and lateral chest radiographs. Acad Radiol. 2007 Jan; 14(1):28-37.
    View in: PubMed
    Score: 0.074
  18. Computerized detection of vertebral compression fractures on lateral chest radiographs: preliminary results with a tool for early detection of osteoporosis. Med Phys. 2006 Dec; 33(12):4664-74.
    View in: PubMed
    Score: 0.074
  19. Computer-aided diagnosis for the detection and classification of lung cancers on chest radiographs ROC analysis of radiologists' performance. Acad Radiol. 2006 Aug; 13(8):995-1003.
    View in: PubMed
    Score: 0.072
  20. Integrating PET and CT information to improve diagnostic accuracy for lung nodules: A semiautomatic computer-aided method. J Nucl Med. 2006 Jul; 47(7):1075-80.
    View in: PubMed
    Score: 0.072
  21. Computer-aided diagnosis in thoracic CT. Semin Ultrasound CT MR. 2005 Oct; 26(5):357-63.
    View in: PubMed
    Score: 0.068
  22. Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network. IEEE Trans Med Imaging. 2005 Sep; 24(9):1138-50.
    View in: PubMed
    Score: 0.068
  23. Effect of temporal subtraction images on radiologists' detection of lung cancer on CT: results of the observer performance study with use of film computed tomography images. Acad Radiol. 2004 Dec; 11(12):1337-43.
    View in: PubMed
    Score: 0.064
  24. Computerized scheme for automated detection of lung nodules in low-dose computed tomography images for lung cancer screening. Acad Radiol. 2004 Jun; 11(6):617-29.
    View in: PubMed
    Score: 0.062
  25. Artificial neural networks (ANNs) for differential diagnosis of interstitial lung disease: results of a simulation test with actual clinical cases. Acad Radiol. 2004 Jan; 11(1):29-37.
    View in: PubMed
    Score: 0.060
  26. Investigation of new psychophysical measures for evaluation of similar images on thoracic computed tomography for distinction between benign and malignant nodules. Med Phys. 2003 Oct; 30(10):2584-93.
    View in: PubMed
    Score: 0.059
  27. Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography. Med Phys. 2003 Sep; 30(9):2440-54.
    View in: PubMed
    Score: 0.059
  28. Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography. Med Phys. 2003 Jul; 30(7):1602-17.
    View in: PubMed
    Score: 0.058
  29. Computerized scheme for determination of the likelihood measure of malignancy for pulmonary nodules on low-dose CT images. Med Phys. 2003 Mar; 30(3):387-94.
    View in: PubMed
    Score: 0.057
  30. 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: 0.056
  31. 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: 0.016
  32. 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: 0.015
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.