We examine the noise advantages of having a computed tomography (CT) detector whose spatial resolution is significantly better (e.g. a factor of 2) than needed for a desired resolution in the reconstructed images. The effective resolution of detectors in x-ray CT is sometimes degraded by binning cells because the small cell size and fine sampling are not needed to achieve the desired resolution (e.g. with flat panel detectors). We studied the effect of the binning process on the noise in the reconstructed images and found that while the images in the absence of noise can be made identical for the native and the binned system, for the same system MTF in the presence of noise, the binned system always results in noisier reconstructed images. The effect of the increased noise in the reconstructed images on lesion detection is scale (frequency content) dependent with a larger difference between the high resolution and binned systems for imaging fine structure (small objects). We show simulated images reconstructed with both systems for representative objects and quantify the impact of the noise on the detection of the lesions based on mathematical observers. Through both subjective assessment of the reconstructed images and the quantification using mathematical observers, we show that for a CT system where the photon noise is dominant, higher resolution in the detectors leads to better noise performance in the reconstructed images at any resolution.
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