AffiliationUniv Arizona, Coll Opt Sci
MetadataShow full item record
PublisherSPIE-INT SOC OPTICAL ENGINEERING
CitationKupinski, M. A., Garrett, Z., & Fan, J. (2020, March). Observer-driven texture analysis in CT imaging. In Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment (Vol. 11316, p. 1131610). International Society for Optics and Photonics.
Rights© 2020 SPIE
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractWe have implemented a technique for analyzing and characterizing the textures in medical images. This technique generates a list of characteristic textures and sorts them from most important to least important for the task of detecting a specific signal in the image. The effects of the human-visual system can be incorporated into this method through the use of an eye filter. The final set of sorted textures can be quickly utilized to analyze new sets of images and make comparison regarding performance on the same task. This analysis is based upon whether the new set of images contains textures that are similar or dissimilar to that of the original set of images. We present the method for analyzing and sorting textures based on how well signals can be distinguished. We also discuss the importance of the most "obscuring" textures that make signal-detection difficult. Results and comparisons of task performance are presented.