Projection-Space Model Observers Based on Marginal Linear Discriminants

Past studies with tomographic reconstructions have shown that visual-search (VS) model observers can be used to evaluate acquisition protocols in medical imaging. However, projection-space studies could be more efficient. A localization ROC (LROC) study was conducted with two VS observers and sets of simulated CT projections and reconstructions generated from a clinically realistic 2D lumbar-spine phantom. The phantom was an axial slice through the L3 vertebrae of a clinical CT. Simulated 1-cm circular lesions had a relative contrast of 1.5. The acquisitions contained from 15 to 512 parallel-beam projections over 180 degrees. Reconstructions were generated with backprojection (BP) and filtered BP (FBP). Both observers identified and compared suspicious candidate locations in an image by means of feature extraction. One observer used the lesion gradient while the other used the gradients for a set of approximate lesion profiles. Observer performance with projections and BP images was highly correlated as a function of the number of projections. FBP performance was lower but still correlated with projection and BP-image performance. VS observers may provide a novel means of optimizing CT acquisitions under clinically relevant tasks using projection data.