In tomographic medical imaging, signal activity is typically estimated by summing voxels from a reconstructed image. We introduce an alternative estimation scheme that operates on the raw projection data and offers a substantial improvement, as measured by the ensemble mean-square error (EMSE), when compared to using voxel values from a reconstruction. The scanning-linear (SL) estimator operates on the raw projection data and is derived as a special case of maximum-likelihood (ML) estimation with a series of approximations to make the calculation tractable. Conventional estimation algorithms that operate on reconstructed data are subject to unpredictable bias arising from the null functions of the imaging system. To show that the bias in ROI estimates affects not only absolute values but also relative differences, such as those used to monitor response to therapy, the activity estimation task is repeated for three different signal sizes.

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