Extensive research has shown that practice yields highly specific perceptual learning of simple visual properties such as orientation and contrast. Does this same learning characterize more complex perceptual skills? Here we investigated perceptual learning of complex medical images. Novices underwent training over four sessions to discriminate which of two chest radiographs contained a tumor and to indicate the location of the tumor. In training, one group received six repetitions of 30 normal/abnormal images, the other three repetitions of 60 normal/abnormal images. Groups were then tested on trained and novel images. To assess the nature of perceptual learning, test items were presented in three formats – the full image, the cutout of the tumor, or the background only. Performance improved across training sessions, and notably, the improvement transferred to the classification of novel images. Training with more repetitions on fewer images yielded comparable transfer to training with fewer repetitions on more images. Little transfer to novel images occurred when tested with just the cutout of the cancer region or just the background, but a larger cutout that included both the cancer region and some surrounding regions yielded good transfer. Perceptual learning contributes to the acquisition of expertise in cancer image perception.
Bibliographical noteFunding Information:
Images used in this study were obtained from the Japanese Society of Radiological Technology Database (Shiraishi et al., 2000), accessible at http://db.jsrt.or.jp/eng.php. We thank Dr David Nascene for suggestions about the task, Yingchen He for help with data collection, and Caitlin Sisk for comments and suggestions. Correspondence should be directed to Sha Li or Yuhong Jiang, 75 East River Road, S506 Elliott Hall, Minneapolis, MN 55455, USA. Email: firstname.lastname@example.org or email@example.com.
This study was supported by a dissertation research fellowship from the American Psychological Association to Sha Li, and by a seed grant from OFAA-Social Sciences at the University of Minnesota. Acknowledgments
© 2020, The Author(s).
- Lung Neoplasms/diagnosis
- Pattern Recognition, Visual/physiology
- Practice, Psychological
- Young Adult
PubMed: MeSH publication types
- Research Support, Non-U.S. Gov't
- Journal Article