Sparse-view tomography has many applications such as in low-dose computed tomography(CT).Using undersampled data,a perfect image is not expected.The goal of this paper is to obtain a tomographic image that is better ...Sparse-view tomography has many applications such as in low-dose computed tomography(CT).Using undersampled data,a perfect image is not expected.The goal of this paper is to obtain a tomographic image that is better than the naïve filtered backprojection(FBP)reconstruction that uses linear interpolation to complete the measurements.This paper proposes a method to estimate the un-measured projections by displacement function interpolation.Displacement function estimation is a non-linear procedure and the linear interpolation is performed on the displacement function(instead of,on the sinogram itself).As a result,the estimated measurements are not the linear transformation of the measured data.The proposed method is compared with the linear interpolation methods,and the proposed method shows superior performance.展开更多
基金This research is partially supported by NIH grant R15EB024283.
文摘Sparse-view tomography has many applications such as in low-dose computed tomography(CT).Using undersampled data,a perfect image is not expected.The goal of this paper is to obtain a tomographic image that is better than the naïve filtered backprojection(FBP)reconstruction that uses linear interpolation to complete the measurements.This paper proposes a method to estimate the un-measured projections by displacement function interpolation.Displacement function estimation is a non-linear procedure and the linear interpolation is performed on the displacement function(instead of,on the sinogram itself).As a result,the estimated measurements are not the linear transformation of the measured data.The proposed method is compared with the linear interpolation methods,and the proposed method shows superior performance.
