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Connection

Kunio Doi to Breast Neoplasms

This is a "connection" page, showing publications Kunio Doi has written about Breast Neoplasms.
Connection Strength

2.184
  1. Usefulness of presentation of similar images in the diagnosis of breast masses on mammograms: comparison of observer performances in Japan and the USA. Radiol Phys Technol. 2013 Jan; 6(1):70-7.
    View in: PubMed
    Score: 0.165
  2. Evaluation of objective similarity measures for selecting similar images of mammographic lesions. J Digit Imaging. 2011 Feb; 24(1):75-85.
    View in: PubMed
    Score: 0.148
  3. Presentation of similar images as a reference for distinction between benign and malignant masses on mammograms: analysis of initial observer study. J Digit Imaging. 2010 Oct; 23(5):592-602.
    View in: PubMed
    Score: 0.138
  4. Potential usefulness of similar images in the differential diagnosis of clustered microcalcifications on mammograms. Radiology. 2009 Dec; 253(3):625-31.
    View in: PubMed
    Score: 0.135
  5. Determination of similarity measures for pairs of mass lesions on mammograms by use of BI-RADS lesion descriptors and image features. Acad Radiol. 2009 Apr; 16(4):443-9.
    View in: PubMed
    Score: 0.131
  6. Investigation of psychophysical similarity measures for selection of similar images in the diagnosis of clustered microcalcifications on mammograms. Med Phys. 2008 Dec; 35(12):5695-702.
    View in: PubMed
    Score: 0.128
  7. 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: 0.124
  8. Determination of subjective similarity for pairs of masses and pairs of clustered microcalcifications on mammograms: comparison of similarity ranking scores and absolute similarity ratings. Med Phys. 2007 Jul; 34(7):2890-5.
    View in: PubMed
    Score: 0.116
  9. An improved computer-aided diagnosis scheme using the nearest neighbor criterion for determining histological classification of clustered microcalcifications. Methods Inf Med. 2007; 46(6):716-22.
    View in: PubMed
    Score: 0.112
  10. Computer-aided diagnosis scheme for identifying histological classification of clustered microcalcifications by use of follow-up magnification mammograms. Acad Radiol. 2006 Oct; 13(10):1219-28.
    View in: PubMed
    Score: 0.110
  11. Investigation of psychophysical measure for evaluation of similar images for mammographic masses: preliminary results. Med Phys. 2005 Jul; 32(7):2295-304.
    View in: PubMed
    Score: 0.101
  12. Computer-aided diagnosis scheme for histological classification of clustered microcalcifications on magnification mammograms. Med Phys. 2004 Apr; 31(4):789-99.
    View in: PubMed
    Score: 0.092
  13. [Intra-arterial infusion chemotherapy with docetaxel for locally advanced breast cancer and inflammatory breast cancer]. Gan To Kagaku Ryoho. 2000 Oct; 27(12):1823-5.
    View in: PubMed
    Score: 0.072
  14. Improving breast cancer diagnosis with computer-aided diagnosis. Acad Radiol. 1999 Jan; 6(1):22-33.
    View in: PubMed
    Score: 0.064
  15. 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: 0.063
  16. 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: 0.062
  17. Automated computerized classification of malignant and benign masses on digitized mammograms. Acad Radiol. 1998 Mar; 5(3):155-68.
    View in: PubMed
    Score: 0.061
  18. Malignant and benign clustered microcalcifications: automated feature analysis and classification. Radiology. 1996 Mar; 198(3):671-8.
    View in: PubMed
    Score: 0.053
  19. Automated segmentation of digitized mammograms. Acad Radiol. 1995 Jan; 2(1):1-9.
    View in: PubMed
    Score: 0.049
  20. Representation of lesion similarity by use of multidimensional scaling for breast masses on mammograms. J Digit Imaging. 2013 Aug; 26(4):740-7.
    View in: PubMed
    Score: 0.044
  21. Usefulness of texture analysis for computerized classification of breast lesions on mammograms. J Digit Imaging. 2007 Sep; 20(3):248-55.
    View in: PubMed
    Score: 0.029
  22. The activity of matrix metalloproteinases (MMPS) and tissue inhibitors of metalloproteinases (TIMPs) in mammary tumors of dogs and rats. J Vet Med Sci. 2006 Feb; 68(2):105-11.
    View in: PubMed
    Score: 0.026
  23. [A trial for neoadjuvant chemotherapy of transarterial infusion of docetaxel in locally advanced breast cancer]. Gan To Kagaku Ryoho. 2000 Jan; 27(1):143-5.
    View in: PubMed
    Score: 0.017
  24. Computer-aided diagnosis in radiology: potential and pitfalls. Eur J Radiol. 1999 Aug; 31(2):97-109.
    View in: PubMed
    Score: 0.017
  25. 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: 0.016
  26. 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: 0.012
  27. 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: 0.012
  28. Computerized detection of masses in digital mammograms: automated alignment of breast images and its effect on bilateral-subtraction technique. Med Phys. 1994 Mar; 21(3):445-52.
    View in: PubMed
    Score: 0.011
  29. 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: 0.011
  30. Effect of case selection on the performance of computer-aided detection schemes. Med Phys. 1994 Feb; 21(2):265-9.
    View in: PubMed
    Score: 0.011
  31. 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: 0.011
  32. 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: 0.011
  33. 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: 0.010
  34. 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: 0.007
  35. Image feature analysis and computer-aided diagnosis in digital radiography. I. Automated detection of microcalcifications in mammography. Med Phys. 1987 Jul-Aug; 14(4):538-48.
    View in: PubMed
    Score: 0.007
  36. 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: 0.003
  37. Computer-aided detection of clustered microcalcifications on digital mammograms. Med Biol Eng Comput. 1995 Mar; 33(2):174-8.
    View in: PubMed
    Score: 0.003
  38. Magnification film mammography: image quality and clinical studies. Radiology. 1977 Oct; 125(1):69-76.
    View in: PubMed
    Score: 0.001
  39. Image quality in mammography. Radiology. 1977 Oct; 125(1):77-85.
    View in: PubMed
    Score: 0.001
  40. The effect of geometric and recording system unsharpness in mammography. Invest Radiol. 1975 Jan-Feb; 10(1):43-52.
    View in: PubMed
    Score: 0.001
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.