Data reconstruction using directional interpolation techniques

• US 8,233,701 B2
• Filed: 09/09/2010
• Issued: 07/31/2012
• Est. Priority Date: 06/13/2003
• Status: Expired due to Fees

• Current Assignee: Ajit Yoganathan, David Frakes, Joseph Monaco, Mark Smith
• Original Assignee: Ajit Yoganathan, David Frakes, Joseph Monaco, Mark Smith
• Inventors: Yoganathan, Ajit, Frakes, David, Monaco, Joseph, Smith, Mark
• Primary Examiner(s): Le, Brian
• Application Number:
  US12/878,366
• Publication Number:
  US 20110002532A1
• Time in Patent Office: 691 Days
• Field of Search: 382/154, 382/199, 382/285, 382/266, 382/173, 382/300, 345/653, 345/654, 345/664, 345/665, 345/679, 345/680, 345/626
• US Class Current: 382/154
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 3/4007 based on interpolation, e.g. bilinear interpolation image demosaicing G06T3/4015; edge-driven or edge-based scaling G06T3/403
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06V 10/245 by locating a pattern; Special marks for positioning
• CPC Class Codes: H04N 19/51 Motion estimation or motion compensation

Abstract

Approaches to three-dimensional (3D) data reconstruction are presented. The 3D data comprises 2D images. In some embodiments, the 2D images are directionally interpolated to generate directionally-interpolated 3D data. The directionally-interpolated 3D data are then segmented to generate segmented directionally-interpolated 3D data. The segmented directionally-interpolated 3D data is then meshed. In other embodiments, a 3D data set, which includes 2D flow images, is accessed. The accessed 2D flow images are then directionally interpolated to generate 2D intermediate flow images.

Claims

1. A computer-implemented method for reconstructing a three-dimensional (3D) data set, the 3D data set comprising 2D images, the method comprising the steps of:

accessing adjacent 2D images; and

directionally interpolating the adjacent 2D images to generate directionally-interpolated 3D data, such that divergence errors associated with the directionally-interpolated 3D data are minimal.

2. The method of claim 1, wherein the 3D data set comprises a 3D morphological data set.

3. The method of claim 1, wherein the 3D data set comprises a 3D velocity data set.

4. The system of claim 3, wherein the 3D velocity data set comprises a 3D magnetic resonance (MR) imaging velocity data set.

5. The method of claim 1, further comprising the step of segmenting the directionally-interpolated 3D data.

6. The method of claim 1, wherein the step of directionally interpolating between adjacent 2D images comprises the step of executing a block-based motion estimation algorithm on the adjacent 2D images.

7. The method of claim 1, wherein the step of directionally interpolating between adjacent 2D images comprises the step of executing an optical flow-based motion estimation algorithm on the adjacent 2D images.

8. The method of claim 1, wherein the step of directionally interpolating between adjacent 2D images comprises the step of executing a control grid interpolation (CGI) algorithm on the adjacent 2D images.

9. The method of claim 1, wherein the step of directionally interpolating between adjacent 2D images comprises the step of executing an adaptive control grid interpolation (ACGI) algorithm on the adjacent 2D images.

10. A non-transitory computer-readable medium having code for reconstructing three-dimensional (3D) data, the 3D data comprising 2D images, the non-transitory computer-readable medium comprising:

computer-readable code adapted to access adjacent 2D images; and

computer-readable code adapted to instruct a programmable device to directionally interpolate between adjacent 2D images to generate directionally-interpolated 3D data, such that divergence errors associated with the directionally-interpolated 3D data are minimal.

11. The non-transitory computer-readable medium of claim 10, wherein the 3D data set is one selected from the group consisting of:

a 3D morphological image;

a 3D velocity data set;

a 3D magnetic resonance (MR) imaging modulus image data set;

an MR velocity imaging data set; and

an MR imaging velocity magnitude data set.

12. The non-transitory computer-readable medium of claim 10, further comprising computer-readable code selected from the group consisting of:

a block-based motion estimation algorithm;

an optical flow-based motion estimation algorithm;

a control grid interpolation (CGI) algorithm; and

an adaptive control grid interpolation (ACGI) algorithm.