Robert Nishikawa to Radiographic Image Interpretation, Computer-Assisted
This is a "connection" page, showing publications Robert Nishikawa has written about Radiographic Image Interpretation, Computer-Assisted.
Connection Strength
3.519
-
A comparison study of image features between FFDM and film mammogram images. Med Phys. 2012 Jul; 39(7):4386-94.
Score: 0.325
-
Re: effectiveness of computer-aided detection in community mammography practice. J Natl Cancer Inst. 2012 Jan 04; 104(1):77; author reply 78-9.
Score: 0.314
-
Comparison of power spectra for tomosynthesis projections and reconstructed images. Med Phys. 2009 May; 36(5):1753-8.
Score: 0.261
-
Computer-aided screening mammography. N Engl J Med. 2007 Jul 05; 357(1):84; author reply 85.
Score: 0.230
-
Computer-aided detection, in its present form, is not an effective aid for screening mammography. For the proposition. Med Phys. 2006 Apr; 33(4):811-2.
Score: 0.211
-
Radial gradient-based segmentation of mammographic microcalcifications: observer evaluation and effect on CAD performance. Med Phys. 2004 Sep; 31(9):2648-57.
Score: 0.189
-
Estimating three-class ideal observer decision variables for computerized detection and classification of mammographic mass lesions. Med Phys. 2004 Jan; 31(1):81-90.
Score: 0.181
-
The use of a priori information in the detection of mammographic microcalcifications to improve their classification. Med Phys. 2003 May; 30(5):823-31.
Score: 0.172
-
A support vector machine approach for detection of microcalcifications. IEEE Trans Med Imaging. 2002 Dec; 21(12):1552-63.
Score: 0.168
-
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.
Score: 0.118
-
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.
Score: 0.115
-
Comment on "Quantitative classification of breast tumors in digitized mammograms" [Med. Phys. 23, 1337-1345 (1996)]. Med Phys. 1997 Feb; 24(2):313, 315.
Score: 0.112
-
Computer-aided detection of clustered microcalcifications on digital mammograms. Med Biol Eng Comput. 1995 Mar; 33(2):174-8.
Score: 0.098
-
Analysis of perceived similarity between pairs of microcalcification clusters in mammograms. Med Phys. 2014 May; 41(5):051904.
Score: 0.092
-
Computer-aided detection of clustered microcalcifications: an improved method for grouping detected signals. Med Phys. 1993 Nov-Dec; 20(6):1661-6.
Score: 0.089
-
Retrieval boosted computer-aided diagnosis of clustered microcalcifications for breast cancer. Med Phys. 2012 Feb; 39(2):676-85.
Score: 0.079
-
Automated detection of mass lesions in dedicated breast CT: a preliminary study. Med Phys. 2012 Feb; 39(2):866-73.
Score: 0.079
-
On the orientation of mammographic structure. Med Phys. 2011 Oct; 38(10):5303-6.
Score: 0.077
-
Automated detection of microcalcification clusters for digital breast tomosynthesis using projection data only: a preliminary study. Med Phys. 2008 Apr; 35(4):1486-93.
Score: 0.061
-
Identification of simulated microcalcifications in white noise and mammographic backgrounds. Med Phys. 2006 Aug; 33(8):2905-11.
Score: 0.054
-
Computerized mass detection for digital breast tomosynthesis directly from the projection images. Med Phys. 2006 Feb; 33(2):482-91.
Score: 0.052
-
Relevance vector machine for automatic detection of clustered microcalcifications. IEEE Trans Med Imaging. 2005 Oct; 24(10):1278-85.
Score: 0.051
-
A study on several machine-learning methods for classification of malignant and benign clustered microcalcifications. IEEE Trans Med Imaging. 2005 Mar; 24(3):371-80.
Score: 0.049
-
A similarity learning approach to content-based image retrieval: application to digital mammography. IEEE Trans Med Imaging. 2004 Oct; 23(10):1233-44.
Score: 0.048
-
Investigation of physical image quality indices of a bone densitometry system. Med Phys. 2004 Apr; 31(4):873-81.
Score: 0.046
-
Computer-aided detection and diagnosis of breast cancer. Radiol Clin North Am. 2000 Jul; 38(4):725-40.
Score: 0.035
-
Analysis of methods for reducing false positives in the automated detection of clustered microcalcifications in mammograms. Med Phys. 1998 Aug; 25(8):1502-6.
Score: 0.031
-
An improved shift-invariant artificial neural network for computerized detection of clustered microcalcifications in digital mammograms. Med Phys. 1996 Apr; 23(4):595-601.
Score: 0.026
-
Malignant and benign clustered microcalcifications: automated feature analysis and classification. Radiology. 1996 Mar; 198(3):671-8.
Score: 0.026
-
Toward consensus on quantitative assessment of medical imaging systems. Med Phys. 1995 Jul; 22(7):1057-61.
Score: 0.025
-
Clinical use of digital mammography: the present and the prospects. J Digit Imaging. 1995 Feb; 8(1 Suppl 1):74-9.
Score: 0.024
-
Algorithmic scatter correction in dual-energy digital mammography. Med Phys. 2013 Nov; 40(11):111919.
Score: 0.022
-
An "intelligent" workstation for computer-aided diagnosis. Radiographics. 1993 May; 13(3):647-56.
Score: 0.022
-
Computer-aided diagnosis: development of automated schemes for quantitative analysis of radiographic images. Semin Ultrasound CT MR. 1992 Apr; 13(2):140-52.
Score: 0.020
-
Dependence of computer classification of clustered microcalcifications on the correct detection of microcalcifications. Med Phys. 2001 Sep; 28(9):1949-57.
Score: 0.010
-
Density correction of peripheral breast tissue on digital mammograms. Radiographics. 1996 Nov; 16(6):1403-11.
Score: 0.007