As anatomical noise is often a dominating factor affecting signal detection in medical imaging, we investigate the effects of anatomical backgrounds on signal detection in volumetric cone beam CT images. Signal detection performances are compared between transverse and longitudinal planes with either uniform or anatomical backgrounds. Sphere objects with diameters of lmm, 5mm, 8mm, and 1 lmm are used as the signals. Three-dimensional (3D) anatomical backgrounds are generated using an anatomical noise power spectrum, 1/f~β, with β=3, equivalent to mammographic background. The mean voxel value of the 3D anatomical backgrounds is used as an attenuation coefficient of the uniform background. Noisy projection data are acquired by the forward projection of the uniform and anatomical 3D backgrounds with/without sphere lesions and by the addition of quantum noise. Then, images are reconstructed by an FDK algorithm . For each signal size, signal detection performances in transverse and longitudinal planes are measured by calculating the task SNR of a channelized Hotelling observer with Laguerre-Gauss channels. In the uniform background case, transverse planes yield higher task SNR values for all sphere diameters but lmm. In the anatomical background case, longitudinal planes yield higher task SNR values for all signal diameters. The results indicate that it is beneficial to use longitudinal planes to detect spherical signals in anatomical backgrounds.
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