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Connection

Kunio Doi to Diagnostic Imaging

This is a "connection" page, showing publications Kunio Doi has written about Diagnostic Imaging.

 
Connection Strength
 
 
 
2.339
 
  1. Doi K. [ICRU Activities in Medical Imaging Field]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2016 Jun; 72(6):530-6.
    View in: PubMed
    Score: 0.450
  2. Sato M, Ogura T, Yasumoto Y, Kadowaki Y, Hayashi N, Doi K. Development of an image operation system with a motion sensor in dental radiology. Radiol Phys Technol. 2015 Jul; 8(2):243-7.
    View in: PubMed
    Score: 0.417
  3. Doi K. [Needs of research for technologist-assisted diagnosis (TAD)]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2014 Jan; 70(1):86-8.
    View in: PubMed
    Score: 0.381
  4. Shiraishi J, Pesce LL, Metz CE, Doi K. Experimental design and data analysis in receiver operating characteristic studies: lessons learned from reports in radiology from 1997 to 2006. Radiology. 2009 Dec; 253(3):822-30.
    View in: PubMed
    Score: 0.285
  5. Doi K. Computer-aided diagnosis in medical imaging: historical review, current status and future potential. Comput Med Imaging Graph. 2007 Jun-Jul; 31(4-5):198-211.
    View in: PubMed
    Score: 0.237
  6. Li Q, Doi K. Comparison of typical evaluation methods for computer-aided diagnostic schemes: Monte Carlo simulation study. Med Phys. 2007 Mar; 34(3):871-6.
    View in: PubMed
    Score: 0.237
  7. Doi K. Diagnostic imaging over the last 50 years: research and development in medical imaging science and technology. Phys Med Biol. 2006 Jul 07; 51(13):R5-27.
    View in: PubMed
    Score: 0.226
  8. Hoffmann KR, Chen CT, Doi K. Automated region identification and its application to measuring cardiac function. Am J Card Imaging. 1991 Dec; 5(4):272-80.
    View in: PubMed
    Score: 0.082
  9. Wu Y, Doi K, Metz CE, Asada N, Giger ML. Simulation studies of data classification by artificial neural networks: potential applications in medical imaging and decision making. J Digit Imaging. 1993 May; 6(2):117-25.
    View in: PubMed
    Score: 0.023
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.