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Connection

Hiroyuki Abe to Observer Variation

This is a "connection" page, showing publications Hiroyuki Abe has written about Observer Variation.
Connection Strength

0.462
  1. Discrimination of benign from malignant breast lesions in dense breasts with model-based analysis of regions-of-interest using directional diffusion-weighted images. BMC Med Imaging. 2020 06 09; 20(1):61.
    View in: PubMed
    Score: 0.157
  2. Effect of temporal subtraction images on radiologists' detection of lung cancer on CT: results of the observer performance study with use of film computed tomography images. Acad Radiol. 2004 Dec; 11(12):1337-43.
    View in: PubMed
    Score: 0.054
  3. Artificial neural networks (ANNs) for differential diagnosis of interstitial lung disease: results of a simulation test with actual clinical cases. Acad Radiol. 2004 Jan; 11(1):29-37.
    View in: PubMed
    Score: 0.050
  4. Test-retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial. J Magn Reson Imaging. 2019 06; 49(6):1617-1628.
    View in: PubMed
    Score: 0.035
  5. Cross-sectional relatedness between sentences in breast radiology reports: development of an SVM classifier and evaluation against annotations of five breast radiologists. J Digit Imaging. 2013 Oct; 26(5):977-88.
    View in: PubMed
    Score: 0.025
  6. Observer study of a prototype clinical decision support system for breast cancer diagnosis using dynamic contrast-enhanced MRI. AJR Am J Roentgenol. 2013 Feb; 200(2):277-83.
    View in: PubMed
    Score: 0.024
  7. Evaluation of clinical breast MR imaging performed with prototype computer-aided diagnosis breast MR imaging workstation: reader study. Radiology. 2011 Mar; 258(3):696-704.
    View in: PubMed
    Score: 0.020
  8. Observer study for evaluating potential utility of a super-high-resolution LCD in the detection of clustered microcalcifications on digital mammograms. J Digit Imaging. 2010 Apr; 23(2):161-9.
    View in: PubMed
    Score: 0.018
  9. Computer-aided diagnosis for the detection and classification of lung cancers on chest radiographs ROC analysis of radiologists' performance. Acad Radiol. 2006 Aug; 13(8):995-1003.
    View in: PubMed
    Score: 0.015
  10. Computer-aided detection of peripheral lung cancers missed at CT: ROC analyses without and with localization. Radiology. 2005 Nov; 237(2):684-90.
    View in: PubMed
    Score: 0.014
  11. Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy. AJR Am J Roentgenol. 2004 Nov; 183(5):1209-15.
    View in: PubMed
    Score: 0.013
  12. Effect of high sensitivity in a computerized scheme for detecting extremely subtle solitary pulmonary nodules in chest radiographs: observer performance study. Acad Radiol. 2003 Nov; 10(11):1302-11.
    View in: PubMed
    Score: 0.012
  13. Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography. Med Phys. 2003 Sep; 30(9):2440-54.
    View in: PubMed
    Score: 0.012
  14. [Development of an image processing scheme for chest radiographs using a dot printer]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2002 Sep; 58(9):1268-77.
    View in: PubMed
    Score: 0.011
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.