• DocumentCode
    3427451
  • Title

    Conscious vs. subconscious perception, as a function of radiological expertise

  • Author

    Alzubaidi, Mohammad ; Black, John A., Jr. ; Patel, Ameet ; Panchanathan, Sethuraman

  • Author_Institution
    CUbiC, Arizona State Univ., Tempe, AZ, USA
  • fYear
    2009
  • fDate
    2-5 Aug. 2009
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Radiological images constitute a special class of images that are captured (or computed) for a specific purpose (i.e. diagnosis) and their ldquocorrectrdquo interpretation is vitally important. However, because they are not ldquonaturalrdquo images, radiologists must be trained to visually interpret them. This training involves perceptual learning that is gradually acquired over an extended period of exposure to radiological images. This implicit (subconscious) knowledge is difficult to pass along explicitly (i.e. verbally) to less experienced radiologists. Multimedia technology has the potential to facilitate perceptual learning in new radiologists. However, it is important to have an objective and quantitative method for evaluating the progress of trainees using this approach. This paper proposes an eye-tracker-based metric for determining the level of expertise of a radiologist in training, based on where he/she lies along a scale based on the visual scanning behavior of radiologists, ranging from novice to expert.
  • Keywords
    demography; medical image processing; visual perception; conscious perception; eye-tracker-based metric; radiological expertise; subconscious perception; visual scanning behavior; Biomedical imaging; Displays; Education; Humans; Magnetic resonance imaging; Pathology; Positron emission tomography; Radiology; Retina; X-rays;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer-Based Medical Systems, 2009. CBMS 2009. 22nd IEEE International Symposium on
  • Conference_Location
    Albuquerque, NM
  • ISSN
    1063-7125
  • Print_ISBN
    978-1-4244-4879-1
  • Electronic_ISBN
    1063-7125
  • Type

    conf

  • DOI
    10.1109/CBMS.2009.5255353
  • Filename
    5255353