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Unified iso-SNR approach to task-directed imaging in flat-panel cone-beam CT

The signal-to-noise ratio (SNR) characteristics of volumetric flat-panel cone-beam CT images are investigated theoretically and experimentally. Analytical models of the noise-power spectrum (NPS) and voxel noise developed in the context of conventional, slice-based CT are extended to the fully 3D case. While early models describe well the noise characteristics of 2D tomographic reconstructions for the case of a 1D detector with constant NPS, the fully 3D approach extends classical descriptions to quantify the 3D NPS and voxel noise in a manner that includes: a 2D detector with generalized blue and NPS characteristics, secondary quantum noise in the conversion of incident x-rays, electronics noise, and 3D aliasing. Classical relationships between image SNR and voxel size and 'slice thickness' are found inaccurate in describing the noise characteristics of 3D flat-panel one-beam CT. The relationship is shown instead to depend on the characteristics of the 3D bandwidth integral associated with the 2D detector modulation transfer function and choice of reconstruction filter. Image SNR is investigated experimentally for a low-frequency soft-tissue visualization task using a prototype system for FPI-CBCT and a low-contrast phantom consisting of tissue-equivalent inserts in water. The contrast-to-noise ratio in images of the low-contrast phantom consisting of tissue-equivalent inserts in water. The contrast-to-noise ratio in images of the low-contrast phantom is measured as a function of scatter-to-primary ratio, imaging dose, and spatial resolution in value reconstructions and compared to theoretical expectations. The adaptability of flat-panel cone-beam CT is quantitatively revealed in a task-directed approach that seeks to 'tune' image SNR through knowledgeable selection of dose and spatial resolution in a manner that is consistent with the imaging task and clinical constraints.