Robert Nishikawa to Algorithms
This is a "connection" page, showing publications Robert Nishikawa has written about Algorithms.
Connection Strength
2.421
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Locally adaptive decision in detection of clustered microcalcifications in mammograms. Phys Med Biol. 2018 02 15; 63(4):045014.
Score: 0.356
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CADe for early detection of breast cancer-current status and why we need to continue to explore new approaches. Acad Radiol. 2014 Oct; 21(10):1320-1.
Score: 0.278
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A comparison study of image features between FFDM and film mammogram images. Med Phys. 2012 Jul; 39(7):4386-94.
Score: 0.241
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Comparison of power spectra for tomosynthesis projections and reconstructed images. Med Phys. 2009 May; 36(5):1753-8.
Score: 0.193
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The hypervolume under the ROC hypersurface of "near-guessing" and "near-perfect" observers in N-class classification tasks. IEEE Trans Med Imaging. 2005 Mar; 24(3):293-9.
Score: 0.145
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Radial gradient-based segmentation of mammographic microcalcifications: observer evaluation and effect on CAD performance. Med Phys. 2004 Sep; 31(9):2648-57.
Score: 0.140
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Improving lesion detection in mammograms by leveraging a Cycle-GAN-based lesion remover. Breast Cancer Res. 2024 02 01; 26(1):21.
Score: 0.134
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Automated mammographic breast density estimation using a fully convolutional network. Med Phys. 2018 Mar; 45(3):1178-1190.
Score: 0.089
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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: 0.087
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A computational model to generate simulated three-dimensional breast masses. Med Phys. 2015 Feb; 42(2):1098-118.
Score: 0.072
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Retrieval boosted computer-aided diagnosis of clustered microcalcifications for breast cancer. Med Phys. 2012 Feb; 39(2):676-85.
Score: 0.059
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Automated detection of mass lesions in dedicated breast CT: a preliminary study. Med Phys. 2012 Feb; 39(2):866-73.
Score: 0.059
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Detection of clustered microcalcifications using spatial point process modeling. Phys Med Biol. 2011 Jan 07; 56(1):1-17.
Score: 0.054
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Task-based assessment of breast tomosynthesis: effect of acquisition parameters and quantum noise. Med Phys. 2010 Apr; 37(4):1591-600.
Score: 0.052
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Enhanced imaging of microcalcifications in digital breast tomosynthesis through improved image-reconstruction algorithms. Med Phys. 2009 Nov; 36(11):4920-32.
Score: 0.050
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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: 0.036
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A similarity learning approach to content-based image retrieval: application to digital mammography. IEEE Trans Med Imaging. 2004 Oct; 23(10):1233-44.
Score: 0.035
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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: 0.032
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Maximum likelihood fitting of FROC curves under an initial-detection-and-candidate-analysis model. Med Phys. 2002 Dec; 29(12):2861-70.
Score: 0.031
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A support vector machine approach for detection of microcalcifications. IEEE Trans Med Imaging. 2002 Dec; 21(12):1552-63.
Score: 0.031
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Developing breast lesion detection algorithms for digital breast tomosynthesis: Leveraging false positive findings. Med Phys. 2022 Dec; 49(12):7596-7608.
Score: 0.030
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Computer-aided detection and diagnosis of breast cancer. Radiol Clin North Am. 2000 Jul; 38(4):725-40.
Score: 0.026
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Optimization and FROC analysis of rule-based detection schemes using a multiobjective approach. IEEE Trans Med Imaging. 1998 Dec; 17(6):1089-93.
Score: 0.023
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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.
Score: 0.023
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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: 0.021
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Optimal reconstruction and quantitative image features for computer-aided diagnosis tools for breast CT. Med Phys. 2017 May; 44(5):1846-1856.
Score: 0.021
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Estimating the Accuracy Level Among Individual Detections in Clustered Microcalcifications. IEEE Trans Med Imaging. 2017 05; 36(5):1162-1171.
Score: 0.021
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Automated segmentation of digitized mammograms. Acad Radiol. 1995 Jan; 2(1):1-9.
Score: 0.018
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Analysis of perceived similarity between pairs of microcalcification clusters in mammograms. Med Phys. 2014 May; 41(5):051904.
Score: 0.017
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Algorithmic scatter correction in dual-energy digital mammography. Med Phys. 2013 Nov; 40(11):111919.
Score: 0.017
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Computerized mass detection for digital breast tomosynthesis directly from the projection images. Med Phys. 2006 Feb; 33(2):482-91.
Score: 0.010
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Relevance vector machine for automatic detection of clustered microcalcifications. IEEE Trans Med Imaging. 2005 Oct; 24(10):1278-85.
Score: 0.009
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Radiologists' preferences for digital mammographic display. The International Digital Mammography Development Group. Radiology. 2000 Sep; 216(3):820-30.
Score: 0.007
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Density correction of peripheral breast tissue on digital mammograms. Radiographics. 1996 Nov; 16(6):1403-11.
Score: 0.005