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Connection

Ingrid Reiser to Humans

This is a "connection" page, showing publications Ingrid Reiser has written about Humans.
Connection Strength

0.188
  1. Development of a neonate X-ray phantom for 2D imaging applications using single-tone inkjet printing. Med Phys. 2021 Sep; 48(9):4944-4954.
    View in: PubMed
    Score: 0.026
  2. Portable abdomen radiography: moving to thickness-based protocols. Pediatr Radiol. 2018 02; 48(2):210-215.
    View in: PubMed
    Score: 0.020
  3. Validation of a power-law noise model for simulating small-scale breast tissue. Phys Med Biol. 2013 Sep 07; 58(17):6011-27.
    View in: PubMed
    Score: 0.015
  4. Automated detection of mass lesions in dedicated breast CT: a preliminary study. Med Phys. 2012 Feb; 39(2):866-73.
    View in: PubMed
    Score: 0.013
  5. On the orientation of mammographic structure. Med Phys. 2011 Oct; 38(10):5303-6.
    View in: PubMed
    Score: 0.013
  6. Task-based assessment of breast tomosynthesis: effect of acquisition parameters and quantum noise. Med Phys. 2010 Apr; 37(4):1591-600.
    View in: PubMed
    Score: 0.012
  7. Automated detection of microcalcification clusters for digital breast tomosynthesis using projection data only: a preliminary study. Med Phys. 2008 Apr; 35(4):1486-93.
    View in: PubMed
    Score: 0.010
  8. Computerized mass detection for digital breast tomosynthesis directly from the projection images. Med Phys. 2006 Feb; 33(2):482-91.
    View in: PubMed
    Score: 0.009
  9. 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.
    View in: PubMed
    Score: 0.008
  10. AAPM task group report 305: Guidance for standardization of vendor-neutral reject analysis in radiography. J Appl Clin Med Phys. 2023 May; 24(5):e13938.
    View in: PubMed
    Score: 0.007
  11. A Clinically Optimal Protocol for the Imaging of Enteric Tubes: On the Basis of Radiologist Interpreted Diagnostic Utility and Radiation Dose Reduction. Acad Radiol. 2022 12; 29(12):e279-e288.
    View in: PubMed
    Score: 0.007
  12. High-Resolution Full-3D Specimen Imaging for Lumpectomy Margin Assessment in Breast Cancer. Ann Surg Oncol. 2021 Oct; 28(10):5513-5524.
    View in: PubMed
    Score: 0.006
  13. Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation. Med Image Anal. 2021 07; 71:102061.
    View in: PubMed
    Score: 0.006
  14. Iodine quantification in limited angle tomography. Med Phys. 2020 Oct; 47(10):4906-4916.
    View in: PubMed
    Score: 0.006
  15. Clinical Significance of US Artifacts. Radiographics. 2017 Sep-Oct; 37(5):1408-1423.
    View in: PubMed
    Score: 0.005
  16. Optimal reconstruction and quantitative image features for computer-aided diagnosis tools for breast CT. Med Phys. 2017 May; 44(5):1846-1856.
    View in: PubMed
    Score: 0.005
  17. Effect of comfort pads and incubator design on neonatal radiography. Pediatr Radiol. 2016 Jan; 46(1):112-8.
    View in: PubMed
    Score: 0.004
  18. Local curvature analysis for classifying breast tumors: Preliminary analysis in dedicated breast CT. Med Phys. 2015 Sep; 42(9):5479-89.
    View in: PubMed
    Score: 0.004
  19. Level set segmentation of breast masses in contrast-enhanced dedicated breast CT and evaluation of stopping criteria. J Digit Imaging. 2014 Apr; 27(2):237-47.
    View in: PubMed
    Score: 0.004
  20. Comparison of human and Hotelling observer performance for a fan-beam CT signal detection task. Med Phys. 2013 Mar; 40(3):031104.
    View in: PubMed
    Score: 0.004
  21. Enhanced imaging of microcalcifications in digital breast tomosynthesis through improved image-reconstruction algorithms. Med Phys. 2009 Nov; 36(11):4920-32.
    View in: PubMed
    Score: 0.003
  22. Comparison of power spectra for tomosynthesis projections and reconstructed images. Med Phys. 2009 May; 36(5):1753-8.
    View in: PubMed
    Score: 0.003
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.