| 摘要 |
A method is provided for processing a sequence of sets of 2D projection images of a moving object, wherein the sequence of sets of 2D projection images is obtained by a medical imaging system that is in motion along a trajectory. The method comprises determining a sequence of images which minimize a function dependant on a set of 3D images, a term of fidelity of the sequence of images, a function of spatial and temporal compression of the sequence of images, a compressibility parameter, and a sequence of operators for an approximate modelling of motion. The sequence of operators leads to a compression constraint augmented by partial knowledge of the motion and the minimization comprises defining a decreasing sequence of degrees of compressibility for which an estimation is determined from an initial sequence. |
| 主权项 |
1. A method for processing a sequence of sets of 2D projection images of a moving object, the motion of which is described by a set of positions referenced by t={t1, . . . , tN}, wherein the sequence of sets of 2D projection images is obtained by a medical imaging system that is in motion along a trajectory, wherein each set of 2D projection images is defined by the following equation:
R(tn)f(tn)=p(tn),where tn is the position referenced, p(tn) is a set of 2D projection images, f(tn) is the 3D image of the object at the position referenced, and R(tn) is a projection operator which models the sampling made by the medical imaging system according to its motion along its trajectory for the position referenced, wherein the method comprises:
determining a sequence of images which minimize the function:
J({right arrow over (g)},λ)=λS(M{right arrow over (g)})+Q({right arrow over (g)})where {right arrow over (g)} is a set of 3D images referenced by {right arrow over (g)}={g(t1), . . . , g(tN)}, Q({right arrow over (g)}) is a term of fidelity of the sequence of images, S({right arrow over (g)}) is a function of spatial and temporal compression of the sequence of images, λ is a compressibility parameter, and M is a sequence of operators for an approximate modelling of motion referenced by M={M(t1), . . . , M(tN)}, wherein the sequence of operators leads to a compression constraint augmented by partial knowledge of the motion S(M{right arrow over (g)}) where M{right arrow over (g)}={M(t1)g(t1), . . . , M(tN)g(tN)};
wherein minimization comprises defining a decreasing sequence of degrees of compressibility for which, an estimation is determined from an initial sequence where {right arrow over (f)}={f(t1), . . . , f(tN)} according to the following equations: {g->0,Λ={λ1,…,λΞ}giveng->(λ1)=Aλ1κ[g->0]g->(λξ)=Aλξκ[g->(λξ-1)]∀ξ∈{2,…,Ξ}g->*(Λ,g->0)=g->(λΞ)where Λ={λ1, . . . , λE} is a decreasing sequence of degrees of compressibility {right arrow over (g)}*(Λ,{right arrow over (g)}0) is the estimation, {right arrow over (g)}0 is the initial sequence, Aλ is an iteration of an algorithm enabling the minimization of J({right arrow over (g)}, λ) relative to {right arrow over (g)} for a fixed λ and Aλκ[{right arrow over (h)}] is a sequence of 3D images resulting from the application of κ iterations of algorithm Aλ to a sequence of 3D images referenced by {right arrow over (h)}. |
