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Connection

Robert Nishikawa to Diagnosis, Computer-Assisted

This is a "connection" page, showing publications Robert Nishikawa has written about Diagnosis, Computer-Assisted.
  1. Importance of Better Human-Computer Interaction in the Era of Deep Learning: Mammography Computer-Aided Diagnosis as a Use Case. J Am Coll Radiol. 2018 01; 15(1 Pt A):49-52.
    View in: PubMed
    Score: 0.507
  2. Point/counterpoint: computer-aided detection should be used routinely to assist screening mammogram interpretation. Med Phys. 2012 Sep; 39(9):5305-7.
    View in: PubMed
    Score: 0.354
  3. Clinically missed cancer: how effectively can radiologists use computer-aided detection? AJR Am J Roentgenol. 2012 Mar; 198(3):708-16.
    View in: PubMed
    Score: 0.342
  4. Computer-aided detection evaluation methods are not created equal. Radiology. 2009 Jun; 251(3):634-6.
    View in: PubMed
    Score: 0.283
  5. Computer-aided detection and diagnosis of breast cancer. Radiol Clin North Am. 2000 Jul; 38(4):725-40.
    View in: PubMed
    Score: 0.152
  6. Computer-aided diagnosis complements full-field digital mammography. Diagn Imaging (San Franc). 1999 Sep; 21(9):47-51, 75.
    View in: PubMed
    Score: 0.144
  7. Optimization and FROC analysis of rule-based detection schemes using a multiobjective approach. IEEE Trans Med Imaging. 1998 Dec; 17(6):1089-93.
    View in: PubMed
    Score: 0.137
  8. Optimal reconstruction and quantitative image features for computer-aided diagnosis tools for breast CT. Med Phys. 2017 May; 44(5):1846-1856.
    View in: PubMed
    Score: 0.122
  9. Effect of case selection on the performance of computer-aided detection schemes. Med Phys. 1994 Feb; 21(2):265-9.
    View in: PubMed
    Score: 0.098
  10. Estimating sensitivity and specificity for technology assessment based on observer studies. Acad Radiol. 2013 Jul; 20(7):825-30.
    View in: PubMed
    Score: 0.093
  11. 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: 0.087
  12. Independent evaluation of computer classification of malignant and benign calcifications in full-field digital mammograms. Acad Radiol. 2007 Mar; 14(3):363-70.
    View in: PubMed
    Score: 0.060
  13. Computerized mass detection for digital breast tomosynthesis directly from the projection images. Med Phys. 2006 Feb; 33(2):482-91.
    View in: PubMed
    Score: 0.056
  14. Comparison of independent double readings and computer-aided diagnosis (CAD) for the diagnosis of breast calcifications. Acad Radiol. 2006 Jan; 13(1):84-94.
    View in: PubMed
    Score: 0.056
  15. Computerized detection of mass lesions in digital breast tomosynthesis images using two- and three dimensional radial gradient index segmentation. Technol Cancer Res Treat. 2004 Oct; 3(5):437-41.
    View in: PubMed
    Score: 0.051
  16. Independent versus sequential reading in ROC studies of computer-assist modalities: analysis of components of variance. Acad Radiol. 2002 Sep; 9(9):1036-43.
    View in: PubMed
    Score: 0.044
  17. Developing breast lesion detection algorithms for digital breast tomosynthesis: Leveraging false positive findings. Med Phys. 2022 Dec; 49(12):7596-7608.
    View in: PubMed
    Score: 0.044
  18. Potential of computer-aided diagnosis to reduce variability in radiologists' interpretations of mammograms depicting microcalcifications. Radiology. 2001 Sep; 220(3):787-94.
    View in: PubMed
    Score: 0.041
  19. Dependence of computer classification of clustered microcalcifications on the correct detection of microcalcifications. Med Phys. 2001 Sep; 28(9):1949-57.
    View in: PubMed
    Score: 0.041
  20. Computer-aided diagnosis in radiology: potential and pitfalls. Eur J Radiol. 1999 Aug; 31(2):97-109.
    View in: PubMed
    Score: 0.036
  21. Improving breast cancer diagnosis with computer-aided diagnosis. Acad Radiol. 1999 Jan; 6(1):22-33.
    View in: PubMed
    Score: 0.034
  22. 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: 0.034
  23. Optimally weighted wavelet transform based on supervised training for detection of microcalcifications in digital mammograms. Med Phys. 1998 Jun; 25(6):949-56.
    View in: PubMed
    Score: 0.033
  24. Quantitative comparison of clustered microcalcifications in for-presentation and for-processing mammograms in full-field digital mammography. Med Phys. 2017 Jul; 44(7):3726-3738.
    View in: PubMed
    Score: 0.031
  25. A computational model to generate simulated three-dimensional breast masses. Med Phys. 2015 Feb; 42(2):1098-118.
    View in: PubMed
    Score: 0.026
  26. Potential usefulness of digital imaging in clinical diagnostic radiology: computer-aided diagnosis. J Digit Imaging. 1995 Feb; 8(1 Suppl 1):2-7.
    View in: PubMed
    Score: 0.026
  27. Clinical use of digital mammography: the present and the prospects. J Digit Imaging. 1995 Feb; 8(1 Suppl 1):74-9.
    View in: PubMed
    Score: 0.026
  28. Automated segmentation of digitized mammograms. Acad Radiol. 1995 Jan; 2(1):1-9.
    View in: PubMed
    Score: 0.026
  29. 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: 0.025
  30. Digital radiography. A useful clinical tool for computer-aided diagnosis by quantitative analysis of radiographic images. Acta Radiol. 1993 Sep; 34(5):426-39.
    View in: PubMed
    Score: 0.024
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.