Robert Nishikawa to Female
This is a "connection" page, showing publications Robert Nishikawa has written about Female.
Connection Strength
0.762
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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: 0.047
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AI in Screening Mammography: Use One Radiologist and Improve Double Reads. Radiology. 2023 11; 309(2):e232964.
Score: 0.046
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Identifying Women With Mammographically- Occult Breast Cancer Leveraging GAN-Simulated Mammograms. IEEE Trans Med Imaging. 2022 01; 41(1):225-236.
Score: 0.041
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Locally adaptive decision in detection of clustered microcalcifications in mammograms. Phys Med Biol. 2018 02 15; 63(4):045014.
Score: 0.031
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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: 0.030
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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: 0.024
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Estimating sensitivity and specificity for technology assessment based on observer studies. Acad Radiol. 2013 Jul; 20(7):825-30.
Score: 0.022
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Point/counterpoint: computer-aided detection should be used routinely to assist screening mammogram interpretation. Med Phys. 2012 Sep; 39(9):5305-7.
Score: 0.021
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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: 0.021
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Clinically missed cancer: how effectively can radiologists use computer-aided detection? AJR Am J Roentgenol. 2012 Mar; 198(3):708-16.
Score: 0.021
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Retrieval boosted computer-aided diagnosis of clustered microcalcifications for breast cancer. Med Phys. 2012 Feb; 39(2):676-85.
Score: 0.020
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Clinical significance of serum growth-regulated oncogene alpha (GROalpha) in patients with gynecological cancer. Eur J Gynaecol Oncol. 2012; 33(2):138-41.
Score: 0.020
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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: 0.020
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On the orientation of mammographic structure. Med Phys. 2011 Oct; 38(10):5303-6.
Score: 0.020
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Detection of clustered microcalcifications using spatial point process modeling. Phys Med Biol. 2011 Jan 07; 56(1):1-17.
Score: 0.019
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Computer-aided detection evaluation methods are not created equal. Radiology. 2009 Jun; 251(3):634-6.
Score: 0.017
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Comparison of power spectra for tomosynthesis projections and reconstructed images. Med Phys. 2009 May; 36(5):1753-8.
Score: 0.017
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Comparison of soft-copy and hard-copy reading for full-field digital mammography. Radiology. 2009 Apr; 251(1):41-9.
Score: 0.017
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Current status and future directions of computer-aided diagnosis in mammography. Comput Med Imaging Graph. 2007 Jun-Jul; 31(4-5):224-35.
Score: 0.015
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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: 0.014
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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: 0.012
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Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis. Radiology. 2023 06; 307(5):e222639.
Score: 0.011
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Use of Artificial Intelligence for Digital Breast Tomosynthesis Screening: A Preliminary Real-world Experience. J Breast Imaging. 2023 May 22; 5(3):258-266.
Score: 0.011
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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: 0.011
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A support vector machine approach for detection of microcalcifications. IEEE Trans Med Imaging. 2002 Dec; 21(12):1552-63.
Score: 0.011
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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: 0.011
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Computer-aided detection and diagnosis of breast cancer. Radiol Clin North Am. 2000 Jul; 38(4):725-40.
Score: 0.009
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Computer-aided diagnosis complements full-field digital mammography. Diagn Imaging (San Franc). 1999 Sep; 21(9):47-51, 75.
Score: 0.009
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Linkage of the ACR National Mammography Database to the Network of State Cancer Registries: Proof of Concept Evaluation by the ACR National Mammography Database Committee. J Am Coll Radiol. 2019 Jan; 16(1):8-14.
Score: 0.008
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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: 0.007
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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: 0.007
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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: 0.007
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Comparison of eye position versus computer identified microcalcification clusters on mammograms. Med Phys. 1997 Jan; 24(1):17-23.
Score: 0.007
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Breast MRI contrast enhancement kinetics of normal parenchyma correlate with presence of breast cancer. Breast Cancer Res. 2016 07 22; 18(1):76.
Score: 0.007
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Local curvature analysis for classifying breast tumors: Preliminary analysis in dedicated breast CT. Med Phys. 2015 Sep; 42(9):5479-89.
Score: 0.007
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Computer-aided detection of clustered microcalcifications on digital mammograms. Med Biol Eng Comput. 1995 Mar; 33(2):174-8.
Score: 0.006
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Computerized detection of clustered microcalcifications: evaluation of performance on mammograms from multiple centers. Radiographics. 1995 Mar; 15(2):443-52.
Score: 0.006
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Clinical use of digital mammography: the present and the prospects. J Digit Imaging. 1995 Feb; 8(1 Suppl 1):74-9.
Score: 0.006
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Using breast radiographers' reports as a second opinion for radiologists' readings of microcalcifications in digital mammography. Br J Radiol. 2015 Mar; 88(1047):20140565.
Score: 0.006
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Analysis of perceived similarity between pairs of microcalcification clusters in mammograms. Med Phys. 2014 May; 41(5):051904.
Score: 0.006
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Effect of case selection on the performance of computer-aided detection schemes. Med Phys. 1994 Feb; 21(2):265-9.
Score: 0.006
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Computer-aided detection of clustered microcalcifications: an improved method for grouping detected signals. Med Phys. 1993 Nov-Dec; 20(6):1661-6.
Score: 0.006
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Algorithmic scatter correction in dual-energy digital mammography. Med Phys. 2013 Nov; 40(11):111919.
Score: 0.006
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The potential of iodine for improving breast cancer diagnosis and treatment. Med Hypotheses. 2013 Jan; 80(1):94-8.
Score: 0.005
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Stereoscopic digital mammography: improved specificity and reduced rate of recall in a prospective clinical trial. Radiology. 2013 Jan; 266(1):81-8.
Score: 0.005
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Assessing the stand-alone sensitivity of computer-aided detection with cancer cases from the Digital Mammographic Imaging Screening Trial. AJR Am J Roentgenol. 2012 Sep; 199(3):W392-401.
Score: 0.005
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Computerized detection of clustered microcalcifications in digital mammograms: applications of artificial neural networks. Med Phys. 1992 May-Jun; 19(3):555-60.
Score: 0.005
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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: 0.005
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Contrast enhancement of hepatic hemangiomas on multiphase MDCT: Can we diagnose hepatic hemangiomas by comparing enhancement with blood pool? AJR Am J Roentgenol. 2010 Aug; 195(2):381-6.
Score: 0.005
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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: 0.004
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Scanned-projection digital mammography. Med Phys. 1987 Sep-Oct; 14(5):717-27.
Score: 0.004
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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: 0.003
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Comparison of independent double readings and computer-aided diagnosis (CAD) for the diagnosis of breast calcifications. Acad Radiol. 2006 Jan; 13(1):84-94.
Score: 0.003
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Relevance vector machine for automatic detection of clustered microcalcifications. IEEE Trans Med Imaging. 2005 Oct; 24(10):1278-85.
Score: 0.003
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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: 0.003
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Signal-to-noise properties of mammographic film-screen systems. Med Phys. 1985 Jan-Feb; 12(1):32-9.
Score: 0.003
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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.
Score: 0.003
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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: 0.003
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Potential of computer-aided diagnosis to reduce variability in radiologists' interpretations of mammograms depicting microcalcifications. Radiology. 2001 Sep; 220(3):787-94.
Score: 0.002
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Dependence of computer classification of clustered microcalcifications on the correct detection of microcalcifications. Med Phys. 2001 Sep; 28(9):1949-57.
Score: 0.002
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Radiologists' preferences for digital mammographic display. The International Digital Mammography Development Group. Radiology. 2000 Sep; 216(3):820-30.
Score: 0.002
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Computer-aided diagnosis in radiology: potential and pitfalls. Eur J Radiol. 1999 Aug; 31(2):97-109.
Score: 0.002
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Improving breast cancer diagnosis with computer-aided diagnosis. Acad Radiol. 1999 Jan; 6(1):22-33.
Score: 0.002
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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: 0.002
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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: 0.002
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Optimally weighted wavelet transform based on supervised training for detection of microcalcifications in digital mammograms. Med Phys. 1998 Jun; 25(6):949-56.
Score: 0.002
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An improved computer-assisted diagnostic scheme using wavelet transform for detecting clustered microcalcifications in digital mammograms. Acad Radiol. 1996 Aug; 3(8):621-7.
Score: 0.002
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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: 0.002
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Malignant and benign clustered microcalcifications: automated feature analysis and classification. Radiology. 1996 Mar; 198(3):671-8.
Score: 0.002
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Triple primary malignant neoplasms including a malignant brain tumor: report of two cases and review of the literature. Surg Neurol. 1996 Mar; 45(3):219-29.
Score: 0.002
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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.
Score: 0.002
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Automated segmentation of digitized mammograms. Acad Radiol. 1995 Jan; 2(1):1-9.
Score: 0.002
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Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network. Med Phys. 1994 Apr; 21(4):517-24.
Score: 0.001
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Digital radiography. A useful clinical tool for computer-aided diagnosis by quantitative analysis of radiographic images. Acta Radiol. 1993 Sep; 34(5):426-39.
Score: 0.001
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[Treatment of metastatic brain tumor from renal cell carcinoma]. No Shinkei Geka. 1990 Oct; 18(10):935-8.
Score: 0.001
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Anthropomorphic radiologic phantoms. Radiology. 1986 Feb; 158(2):550-2.
Score: 0.001