title: A comparison of human and model observers in multislice LROC studies.
abstract: Model and human observers have been compared in a series of localization receiver operating characteristic (LROC) studies involving single-slice and multislice image displays. The task was detection of Ga-avid lymphomas within single photon emission computed tomography (SPECT)-reconstructed transverse slices of a mathematical phantom, and the studies involved four reconstruction strategies: the filtered-backprojection (FBP) and ordered-subset expectation-maximization (OSEM) algorithms with two- and three-dimensional postreconstruction filtering. The human-observer data was drawn from studies performed by Wells et al. (2000), while multiclass versions of the nonprewhitening (NPW), channelized nonprewhitening (CNPW), and channelized Hotelling (CH) model observers, each capable of performing the tumor search task, were applied. The channelized observers were evaluated with multiple square-channel models and both with and without internal noise. For the multislice studies, two different capacities for integrating the slice information were also tested. The CH observer gave good quantitative agreement with the human data from both image-display studies when the internal-noise model was used. The CNPW observer performed similarly with the iterative strategies. Wells et al. had shown that human observers are imperfect integrators of multislice information, and this is characterized as increased internal noise with the model observers.
authors.affiliation: University of Massachusetts Medical School, Worcester, MA 01655, USA.
authors.forename: Howard C
authors.initials: HC
authors.lastname: Gifford
authors.forename: Michael A
authors.initials: MA
authors.lastname: King
authors.forename: P Hendrik
authors.initials: PH
authors.lastname: Pretorius
authors.forename: R Glenn
authors.initials: RG
authors.lastname: Wells
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D002951:Citrates; D003198:Computer Simulation; D005708:Gallium; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008223:Lymphoma / Q000000981:diagnostic imaging*; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods*; D012372:ROC Curve; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods*
chemical_list: D002951:Citrates; D019275:Radiopharmaceuticals; D005708:Gallium; C103850:gallium citrate