Back to results
US 10,896,486 B2Granted
Denoising method and system for preserving clinically significant structures in reconstructed images using adaptively weighted anisotropic diffusion filter
AssigneeToshiba Medical Systems Corporation
InventorsZhi Yang, Michael D. Silver
Life of this patent
Estimating the term…
Abstract
Embodiments and processes of computer tomography perform tasks associated with denoising a reconstructed image using an anisotropic diffusion filter and adaptively weighting an iterative instance of the diffused image based upon the product of a weight value and a difference between the iterative instance of the diffused image and the original image. In general, the adaptive weighting is a negative feedback in the iterative steps.
Claims13
A medical imaging apparatus comprising:
- a processing circuitry configured to execute anisotropic diffusion for medical image data comprising a plurality of signal values, each signal value corresponding to coordinates in a space, the processing circuitry also configured to generate a plurality of weights, wherein the weight for each signal value depends on an edge value corresponding to the coordinates of the respective signal value,
- wherein the processing circuitry repeatedly executes an anisotropic diffusion filter for the medical image data,
- the anisotropic diffusion filter includes a combination of an anisotropic diffusion term and an inhomogeneous term,
- the anisotropic diffusion term applies anisotropic diffusion to a current image, and
- the inhomogeneous term applies the weight to a difference between the current image and an initial image, wherein the anisotropic diffusion filter is given by
- u(tn+1)=u(tn)+(tn+1)−(tn)[∇⋅(D∇u(tn)−u0)]
- where u(tn+1) is a signal value at the (n+1)th iteration, u(tn) is a signal value at the nth iteration, u0 is an initial signal value before application of the anisotropic diffusion filter, D is a diffusion coefficient and W is a weight corresponding to the initial signal value.
4 more elements
A medical image processing method comprising:
- providing medical image data comprising a plurality of signal values, each signal value corresponding to coordinates in a space;
- generating a plurality of weights, wherein the weight for each signal value depends on an edge value corresponding to the coordinates of the respective signal value;
- and
- repeatedly executing an anisotropic diffusion filter for the medical image data,
- wherein the anisotropic diffusion filter includes a combination of an anisotropic diffusion term and an inhomogeneous term,
- the anisotropic diffusion term applies anisotropic diffusion to a current image, and
- the inhomogeneous term applies the weight to a difference between the current image and an initial image, wherein the anisotropic diffusion filter is given by
- u(tn+1)=u(tn)+(tn+1)−(tn)[∇⋅(D∇u(tn)−u0)]
- where u(tn+1) is a signal value at the (n+1)th iteration, u(tn) is a signal value at the nth iteration, u0 is an initial signal value before application of the anisotropic diffusion filter, D is a diffusion coefficient and W is a weight corresponding to the initial signal value.
6 more elements
Dependencies are inferred from the claim text.