Loading...
The University of Chicago Header Logo
Keywords
Last Name
Institution

Connection

Kunio Doi to False Positive Reactions

This is a "connection" page, showing publications Kunio Doi has written about False Positive Reactions.

 
Connection Strength
 
 
 
1.248
 
  1. Li Q, Li F, Doi K. 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: 0.085
  2. Shiraishi J, Li F, Doi K. 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: 0.079
  3. Nie Y, Li Q, Li F, Pu Y, Appelbaum D, Doi K. 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: 0.076
  4. Li Q, Doi K. Analysis and minimization of overtraining effect in rule-based classifiers for computer-aided diagnosis. Med Phys. 2006 Feb; 33(2):320-8.
    View in: PubMed
    Score: 0.074
  5. Arimura H, Li Q, Korogi Y, Hirai T, Katsuragawa S, Yamashita Y, Tsuchiya K, Doi K. Computerized detection of intracranial aneurysms for three-dimensional MR angiography: feature extraction of small protrusions based on a shape-based difference image technique. Med Phys. 2006 Feb; 33(2):394-401.
    View in: PubMed
    Score: 0.074
  6. Suzuki K, Shiraishi J, Abe H, MacMahon H, Doi K. False-positive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network. Acad Radiol. 2005 Feb; 12(2):191-201.
    View in: PubMed
    Score: 0.069
  7. Arimura H, Li Q, Korogi Y, Hirai T, Abe H, Yamashita Y, Katsuragawa S, Ikeda R, Doi K. Automated computerized scheme for detection of unruptured intracranial aneurysms in three-dimensional magnetic resonance angiography. Acad Radiol. 2004 Oct; 11(10):1093-104.
    View in: PubMed
    Score: 0.067
  8. Arimura H, Katsuragawa S, Suzuki K, Li F, Shiraishi J, Sone S, Doi K. 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: 0.066
  9. Abe H, Ashizawa K, Li F, Matsuyama N, Fukushima A, Shiraishi J, MacMahon H, Doi K. 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: 0.064
  10. Li Q, Sone S, Doi K. Selective enhancement filters for nodules, vessels, and airway walls in two- and three-dimensional CT scans. Med Phys. 2003 Aug; 30(8):2040-51.
    View in: PubMed
    Score: 0.062
  11. Suzuki K, Armato SG, Li F, Sone S, Doi K. 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: 0.062
  12. Aoyama M, Li Q, Katsuragawa S, Li F, Sone S, Doi K. 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: 0.060
  13. Masutani Y, MacMahon H, Doi K. Computerized detection of pulmonary embolism in spiral CT angiography based on volumetric image analysis. IEEE Trans Med Imaging. 2002 Dec; 21(12):1517-23.
    View in: PubMed
    Score: 0.059
  14. Anastasio MA, Yoshida H, Nagel R, Nishikawa RM, Doi K. A genetic algorithm-based method for optimizing the performance of a computer-aided diagnosis scheme for detection of clustered microcalcifications in mammograms. Med Phys. 1998 Sep; 25(9):1613-20.
    View in: PubMed
    Score: 0.044
  15. Nagel RH, Nishikawa RM, Papaioannou J, Doi K. Analysis of methods for reducing false positives in the automated detection of clustered microcalcifications in mammograms. Med Phys. 1998 Aug; 25(8):1502-6.
    View in: PubMed
    Score: 0.044
  16. Monnier-Cholley L, MacMahon H, Katsuragawa S, Morishita J, Doi K. Computerized analysis of interstitial infiltrates on chest radiographs: a new scheme based on geometric pattern features and Fourier analysis. Acad Radiol. 1995 Jun; 2(6):455-62.
    View in: PubMed
    Score: 0.035
  17. Li F, Engelmann R, Doi K, Macmahon H. 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: 0.023
  18. Li F, Engelmann R, Doi K, MacMahon H. 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: 0.021
  19. Li F, Engelmann R, Metz CE, Doi K, MacMahon H. 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: 0.021
  20. Armato SG, Roy AS, Macmahon H, Li F, Doi K, Sone S, Altman MB. 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: 0.017
  21. Xu XW, Doi K, Kobayashi T, MacMahon H, Giger ML. Development of an improved CAD scheme for automated detection of lung nodules in digital chest images. Med Phys. 1997 Sep; 24(9):1395-403.
    View in: PubMed
    Score: 0.010
  22. Katsuragawa S, Doi K, MacMahon H, Monnier-Cholley L, Ishida T, Kobayashi T. Classification of normal and abnormal lungs with interstitial diseases by rule-based method and artificial neural networks. J Digit Imaging. 1997 Aug; 10(3):108-14.
    View in: PubMed
    Score: 0.010
  23. Zhang W, Doi K, Giger ML, Nishikawa RM, Schmidt RA. An improved shift-invariant artificial neural network for computerized detection of clustered microcalcifications in digital mammograms. Med Phys. 1996 Apr; 23(4):595-601.
    View in: PubMed
    Score: 0.009
  24. Morishita J, Doi K, Katsuragawa S, Monnier-Cholley L, MacMahon H. Computer-aided diagnosis for interstitial infiltrates in chest radiographs: optical-density dependence of texture measures. Med Phys. 1995 Sep; 22(9):1515-22.
    View in: PubMed
    Score: 0.009
  25. Wu YC, Doi K, Giger ML. Detection of lung nodules in digital chest radiographs using artificial neural networks: a pilot study. J Digit Imaging. 1995 May; 8(2):88-94.
    View in: PubMed
    Score: 0.009
  26. Ema T, Doi K, Nishikawa RM, Jiang Y, Papaioannou J. Image feature analysis and computer-aided diagnosis in mammography: reduction of false-positive clustered microcalcifications using local edge-gradient analysis. Med Phys. 1995 Feb; 22(2):161-9.
    View in: PubMed
    Score: 0.009
  27. Wu YC, Doi K, Giger ML, Metz CE, Zhang W. Reduction of false positives in computerized detection of lung nodules in chest radiographs using artificial neural networks, discriminant analysis, and a rule-based scheme. J Digit Imaging. 1994 Nov; 7(4):196-207.
    View in: PubMed
    Score: 0.008
  28. Zhang W, Doi K, Giger ML, Wu Y, Nishikawa RM, Schmidt RA. Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network. Med Phys. 1994 Apr; 21(4):517-24.
    View in: PubMed
    Score: 0.008
  29. Yin FF, Giger ML, Doi K, Vyborny CJ, Schmidt RA. Computerized detection of masses in digital mammograms: investigation of feature-analysis techniques. J Digit Imaging. 1994 Feb; 7(1):18-26.
    View in: PubMed
    Score: 0.008
  30. Hoffmann KR, MacMahon H, Doi K, Metz CE, Yao L, Abe K. Evaluation of an enhanced digital film-duplication system by receiver operating characteristic analysis. Invest Radiol. 1993 Dec; 28(12):1134-8.
    View in: PubMed
    Score: 0.008
  31. Nishikawa RM, Giger ML, Doi K, Vyborny CJ, Schmidt RA. Computer-aided detection of clustered microcalcifications: an improved method for grouping detected signals. Med Phys. 1993 Nov-Dec; 20(6):1661-6.
    View in: PubMed
    Score: 0.008
  32. Matsumoto T, Yoshimura H, Doi K, Giger ML, Kano A, MacMahon H, Abe K, Montner SM. Image feature analysis of false-positive diagnoses produced by automated detection of lung nodules. Invest Radiol. 1992 Aug; 27(8):587-97.
    View in: PubMed
    Score: 0.007
  33. Matsumoto T, Yoshimura H, Giger ML, Doi K, MacMahon H, Montner SM, Nakanishi T. Potential usefulness of computerized nodule detection in screening programs for lung cancer. Invest Radiol. 1992 Jun; 27(6):471-5.
    View in: PubMed
    Score: 0.007
  34. Wu Y, Doi K, Giger ML, Nishikawa RM. Computerized detection of clustered microcalcifications in digital mammograms: applications of artificial neural networks. Med Phys. 1992 May-Jun; 19(3):555-60.
    View in: PubMed
    Score: 0.007
  35. Yoshimura H, Giger ML, Doi K, MacMahon H, Montner SM. Computerized scheme for the detection of pulmonary nodules. A nonlinear filtering technique. Invest Radiol. 1992 Feb; 27(2):124-9.
    View in: PubMed
    Score: 0.007
  36. Yin FF, Giger ML, Doi K, Metz CE, Vyborny CJ, Schmidt RA. Computerized detection of masses in digital mammograms: analysis of bilateral subtraction images. Med Phys. 1991 Sep-Oct; 18(5):955-63.
    View in: PubMed
    Score: 0.007
  37. Giger ML, Ahn N, Doi K, MacMahon H, Metz CE. Computerized detection of pulmonary nodules in digital chest images: use of morphological filters in reducing false-positive detections. Med Phys. 1990 Sep-Oct; 17(5):861-5.
    View in: PubMed
    Score: 0.006
  38. Chan HP, Vyborny CJ, MacMahon H, Metz CE, Doi K, Sickles EA. Digital mammography. ROC studies of the effects of pixel size and unsharp-mask filtering on the detection of subtle microcalcifications. Invest Radiol. 1987 Jul; 22(7):581-9.
    View in: PubMed
    Score: 0.005
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.