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Connection

Hiroyuki Abe to Radiography, Thoracic

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

0.712
  1. Computer-aided diagnosis in chest radiology. Semin Ultrasound CT MR. 2004 Oct; 25(5):432-7.
    View in: PubMed
    Score: 0.208
  2. Computer-aided diagnosis in chest radiography: results of large-scale observer tests at the 1996-2001 RSNA scientific assemblies. Radiographics. 2003 Jan-Feb; 23(1):255-65.
    View in: PubMed
    Score: 0.185
  3. Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN). IEEE Trans Med Imaging. 2006 Apr; 25(4):406-16.
    View in: PubMed
    Score: 0.058
  4. Computer-aided diagnosis in thoracic CT. Semin Ultrasound CT MR. 2005 Oct; 26(5):357-63.
    View in: PubMed
    Score: 0.056
  5. False-positive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network. Acad Radiol. 2005 Feb; 12(2):191-201.
    View in: PubMed
    Score: 0.053
  6. 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: 0.049
  7. [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: 0.045
  8. Use of an artificial neural network to determine the diagnostic value of specific clinical and radiologic parameters in the diagnosis of interstitial lung disease on chest radiographs. Acad Radiol. 2002 Jan; 9(1):13-7.
    View in: PubMed
    Score: 0.043
  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
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.