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Kunio Doi to Ribs

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

Connection Strength
  1. Suzuki K, Abe H, MacMahon H, Doi K. 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: 0.309
  2. Ishigami N, Shinozuka J, Katayama K, Nakayama H, Doi K. Apoptosis in mouse fetuses from dams exposed to T-2 toxin at different days of gestation. Exp Toxicol Pathol. 2001 Feb; 52(6):493-501.
    View in: PubMed
    Score: 0.054
  3. Ishida T, Katsuragawa S, Nakamura K, MacMahon H, Doi K. Iterative image warping technique for temporal subtraction of sequential chest radiographs to detect interval change. Med Phys. 1999 Jul; 26(7):1320-9.
    View in: PubMed
    Score: 0.048
  4. Ishida T, Katsuragawa S, Kobayashi T, MacMahon H, Doi K. Computerized analysis of interstitial disease in chest radiographs: improvement of geometric-pattern feature analysis. Med Phys. 1997 Jun; 24(6):915-24.
    View in: PubMed
    Score: 0.042
  5. Xu XW, Doi K. Image feature analysis for computer-aided diagnosis: accurate determination of ribcage boundary in chest radiographs. Med Phys. 1995 May; 22(5):617-26.
    View in: PubMed
    Score: 0.036
  6. Sanada S, Doi K, MacMahon H. Image feature analysis and computer-aided diagnosis in digital radiography: automated delineation of posterior ribs in chest images. Med Phys. 1991 Sep-Oct; 18(5):964-71.
    View in: PubMed
    Score: 0.028
  7. Powell GF, Doi K, Katsuragawa S. Localization of inter-rib spaces for lung texture analysis and computer-aided diagnosis in digital chest images. Med Phys. 1988 Jul-Aug; 15(4):581-7.
    View in: PubMed
    Score: 0.023
  8. Matsumoto T, Yoshimura H, Doi K, Giger ML, Kano A, MacMahon H, Abe K, Montner SM. Image feature analysis of false-positive diagnoses produced by automated detection of lung nodules. Invest Radiol. 1992 Aug; 27(8):587-97.
    View in: PubMed
    Score: 0.007
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.