Abstract

Radiological images constitute a special class of images that are captured (or computed) for a specific purpose (i.e. diagnosis) and their "correct" interpretation is vitally important. However, because they are not "natural " 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.

Original languageEnglish (US)
Title of host publication2009 22nd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2009
DOIs
StatePublished - Nov 23 2009
Event2009 22nd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2009 - Albuquerque, NM, United States
Duration: Aug 2 2009Aug 5 2009

Publication series

NameProceedings - IEEE Symposium on Computer-Based Medical Systems
ISSN (Print)1063-7125

Other

Other2009 22nd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2009
CountryUnited States
CityAlbuquerque, NM
Period8/2/098/5/09

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications

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    Alzubaidi, M., Black, J. A., Patel, A., & Panchanathan, S. (2009). Conscious vs. subconscious perception, as a function of radiological expertise. In 2009 22nd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2009 [5255353] (Proceedings - IEEE Symposium on Computer-Based Medical Systems). https://doi.org/10.1109/CBMS.2009.5255353