Feasibility study on aperture-based low-dose CT

In low-dose computed tomography (CT), there is a tradeoff between acquiring an acceptable image quality and reducing delivered dose to the patient in general. Compressive sensing (CS) based iterative image reconstruction algorithms can provide a reasonable image quality under sparse data sampling conditions. In this work, a feasibility study of using a multi-slit aperture for low-dose CT is performed. We implemented an iterative algorithm that utilizes sampling density and data incoherence information to reconstruct the image from sparsely sampled data. We used projection data of a real mouse head, numerically applied a multi-slit aperture to the data, and successfully reconstructed images to an acceptable quality with about 70% dose reduction.