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When a measurement falls outside the quantization or measurable range, itbecomes saturated and cannot be used in classical reconstruction methods. Forexample, in C-arm angiography systems, which provide projection radiography,fluoroscopy, digital subtraction angiography, and are widely used for medicaldiagnoses and interventions, the limited dynamic range of C-arm flat detectorsleads to overexposure in some projections during an acquisition, such asimaging relatively thin body parts (e.g., the knee). Aiming at overexposurecorrection for computed tomography (CT) reconstruction, we in this paperpropose a mixed one-bit compressive sensing (M1bit-CS) to acquire informationfrom both regular and saturated measurements. This method is inspired by therecent progress on one-bit compressive sensing, which deals with only signobservations. Its successful applications imply that information carried bysaturated measurements is useful to improve recovery quality. For the proposedM1bit-CS model, alternating direction methods of multipliers is developed andan iterative saturation detection scheme is established. Then we evaluateM1bit-CS on one-dimensional signal recovery tasks. In some experiments, theperformance of the proposed algorithms on mixed measurements is almost the sameas recovery on unsaturated ones with the same amount of measurements. Finally,we apply the proposed method to overexposure correction for CT reconstructionon a phantom and a simulated clinical image. The results are promising, as thetypical streaking artifacts and capping artifacts introduced by saturatedprojection data are effectively reduced, yielding significant error reductioncompared with existing algorithms based on extrapolation.

Mixed one-bit compressive sensing with applications to overexposure correction for CT reconstruction