Highly accurate and efficient forward and back projection methods for computed tomography
AssigneeUniversity of Florida Research Foundation, Inc.
InventorsAlireza Entezari, Kai Zhang
Life of this patent
Estimating the term…
Abstract
An image is reconstructed an image from projection data by an image reconstruction computing entity. Projection data captured by an imaging device is received. An image is reconstructed and/or generated based at least in part on the projection data using a forward and back projection technique employing a convolutional spline process. The image is provided such that a user computing entity receives the image. The user computing entity is configured to display the image via a user interface thereof.
Claims20
A method for reconstructing an image from projection data by an image reconstruction computing entity, the method comprising:
- receiving, by the image reconstruction computing entity, projection data captured by an imaging device;
- reconstructing, by the image reconstruction computing entity, an image based at least in part on the projection data using a forward and back projection technique employing a convolutional spline process, wherein the convolution spline process comprises:
- computing projected coordinates of 2-D pixels and 3-D voxels on a detector plane,
- computing 1-D footprints on the detector plane of the pixels as a first convolutional spline,
- computing 2-D footprints on the detector plane of voxels as a second convolutional spline,
- approximating 1-D detector blur of pixels by convolving the 1-D footprints with a blur function modeled as a third convolutional spline,
- approximating 2-D detector blur of voxels by convolving the 2-D footprints with a blur function modeled using a fourth convolutional spline, and
- determining the contributions of at least one of the pixels or the voxels to a detector bin using weighted sums of evaluation of the first, second, third, and fourth convolutional splines according to the projected coordinates;
- and
- providing, by the image reconstruction computing entity, the image such that a user computing entity receives the image, the user computing entity configured to display the image via a user interface thereof.
An apparatus comprising at least one processor, a communications interface configured for communicating via at least one network, and at least one memory storing computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least:
- receive projection data captured by an imaging device;
- reconstruct an image based at least in part on the projection data using a forward and back projection technique employing a convolutional spline process, wherein the convolution spline process comprises:
- computing projected coordinates of 2-D pixels and 3-D voxels on a detector plane,
- computing 1-D footprints on the detector plane of the pixels as a first convolutional spline,
- computing 2-D footprints on the detector plane of voxels as a second convolutional spline,
- approximating 1-D detector blur of pixels by convolving the 1-D footprints with a blur function modeled as a third convolutional spline,
- approximating 2-D detector blur of voxels by convolving the 2-D footprints with a blur function modeled using a fourth convolutional spline, and
- determining the contributions of at least one of the pixels or the voxels to a detector bin using weighted sums of evaluation of the first, second, third, and fourth convolutional splines according to the projected coordinates;
- and
- provide the image such that a user computing entity receives the image, the user computing entity configured to display the image via a user interface thereof.
A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising executable portions configured, when executed by a processor of an apparatus, to cause the apparatus to:
- receive projection data captured by an imaging device;
- reconstruct an image based at least in part on the projection data using a forward and back projection technique employing a convolutional spline process, wherein the convolution spline process comprises:
- computing projected coordinates of 2-D pixels and 3-D voxels on a detector plane,
- computing 1-D footprints on the detector plane of the pixels as a first convolutional spline,
- computing 2-D footprints on the detector plane of voxels as a second convolutional spline,
- approximating 1-D detector blur of pixels by convolving the 1-D footprints with a blur function modeled as a third convolutional spline,
- approximating 2-D detector blur of voxels by convolving the 2-D footprints with a blur function modeled using a fourth convolutional spline, and
- determining the contributions of at least one of the pixels or the voxels to a detector bin using weighted sums of evaluation of the first, second, third, and fourth convolutional splines according to the projected coordinates;
- and
- provide the image such that a user computing entity receives the image, the user computing entity configured to display the image via a user interface thereof.
Dependencies are inferred from the claim text.