Lung nodules detection in chest radiography: Image components analysis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We aimed to evaluate the effect of different components of chest image on performances of both human observer and channelized Fisher-Hotelling model (CFH) in nodule detection task. Irrelevant and relevant components were separated from clinical chest radiography by employing Principal Component Analysis (PCA) methods. Human observer performance was evaluated in two-alternative forced-choice (2AFC) on original clinical images and anatomical structure only images obtained by PCA methods. Channelized Fisher-Hotelling model with Laguerre-Gauss basis function was evaluated to predict human performance. We show that relevant component is the primary factor influencing on nodule detection in chest radiography. There is obvious difference of detectability between human observer and CFH model for nodule detection in images only containing anatomical structure. CFH model should be used more carefully.

Original languageEnglish
Title of host publicationMedical Imaging 2009
Subtitle of host publicationImage Perception, Observer Performance, and Technology Assessment
DOIs
StatePublished - 2009
EventMedical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment - Lake Buena Vista, FL, United States
Duration: 11 Feb 200912 Feb 2009

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7263
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment
Country/TerritoryUnited States
CityLake Buena Vista, FL
Period11/02/0912/02/09

Keywords

  • 2AFC
  • Image quality
  • Observer model
  • PCA

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