A comparison of human observer LROC and numerical observer ROC for tumor detection in SPECT images

The authors have compared performances of humans in a localization ROC (LROC) study to performances of a channelized Hotelling observer (CHO) in a "signal-known- exactly" (SKE) ROC study. The task was tumor detection in simulated Ga-67 scans of the chest. The study variables tested by the observer studies were different filtering strategies created by varying the dimensionality and cut-off frequency of a 5th-order Butterworth filter used to smooth the images. Image reconstruction involved filtered backprojection (FBP) with multiplicative Chang attenuation correction. A total of 35 tumor locations were used. Human LROC results for 4 participants were acquired from a preliminary study of 140 images per strategy and a main study of 204 images per strategy. The LROC ratings are given as areas under the LROC curve. For the ROC study, a constant-Q channel model was used, with parameters determined from a previous comparison of human and CHO performance in a SKE ROC study. The CHO was applied to 200 noise realizations per location and strategy. The CHO ratings of the filtering strategies are given as areas under the ROC curve averaged over location. Correlation between the ROC and LROC rankings of the strategies indicates that the CHO may be of use in LROC study design.