CT, PET, MRI, EPRI Image Reconstruction Algorithm for Medical and Security Imaging

University of Chicago
posted on 04/25/2011

The backprojection-filtration (BPF) chord-based image reconstruction algorithm on minimal datasets uses cone-beam projections along helical, circular, or linear trajectories to analytically reconstruct 2D and 3D images.

Suggested Uses

The BPF algorithm can replace legacy image reconstruction algorithms in medical and security imaging devices.


The chord-based BPF image reconstruction algorithm on minimal data sets reduces scan time, patient exposure to radiation, and computational time, and it improves spatial and temporal resolution by minimizing motion contaminated data.

Innovation Details

Detailed Description

CT, PET, MRI, EPRI, and other imaging techniques rely on iterative or analytic image reconstruction algorithms to convert raw scan data into a 2D or 3D image. To reduce scanning and computational time, thereby enabling real-time targeted imaging, Prof. Xiaochuan Pan and his laboratory have developed an analytic chord-based BPF algorithm that requires only a minimum dataset to exactly reconstruct a region of interest. The algorithms are compatible with a variety of source trajectory scan geometries and can minimize motion contamination in an image by the judicious selection of the minimum dataset.

Applications include
  • Radio-therapy on-board imaging,
  • Specimen/Sample radiography,
  • Specialized diagnostic devices,
  • O-arm imaging,
  • Airport security screening,
  • Container shipment screening,
  • Non-destructive testing,
  • and the large diagnostic CT market.

La Riviere P, Vargas P, Xia D, Pan X. Region of interest reconstruction in x-ray fluorescence computed tomography for negligible attenuation. IEEE Trans Nucl Sci. 2010;57(1):234-241.

Cho S, Xia D, Pellizzari CA, Pan X. A BPF-FBP tandem algorithm for image reconstruction in reverse helical cone-beam CT. Med Phys. 2010;37(1):32-9.

Bian J, Xia D, Sidky EY, Pan X. Region of Interest Imaging for a General Trajectory with the Rebinned BPF Algorithm. Tsinghua Sci Technol. 2010;15(1):68-73.

Pan X, Sidky EY, Vannier M. Why do commercial CT scanners still employ traditional, filtered back-projection for image reconstruction? Inverse Probl. 2009;25(12):1230009.

Cho S, Pearson E, Pelizzari CA, Pan X. Region-of-interest image reconstruction with intensity weighting in circular cone-beam CT for image-guided radiation therapy. Med Phys. 2009;36(4):1184-92.

Xia D, Cho S, Pan X. Image reconstruction in reduced circular sinusoidal cone-beam CT. J Xray Sci Technol. 2009;17(3):189-205.

Cho S, Xia D, Pellizzari CA, Pan X. Exact reconstruction of volumetric images in reverse helical cone-beam CT. Med Phys. 2008;35(7):3030-40.

M. King, X. Pan, L. Yu, and M. Giger, ROI reconstruction of motion-contaminated data using a weighted backprojection-filtration algorithm. Med. Phys., 33:1222-1238, 2006.

Yu Zou, Xiaochuan Pan, and Emil Y. Sidky Theory and algorithms for image reconstruction on chords and within regions of interest JOSA A, Vol. 22, Issue 11, pp. 2372-2384 (2005).

Y. Zou, X. Pan, and E. Sidky. Exact image reconstruction on chords from data acquired with a general scanning trajectory. J. Opt. Am. Soc., 22:2372-2384, 2005.

X. Pan, L. Yu, and C.-M. Kao. Image-resolution enhancement in computed tomography. IEEE Trans. Med. Imaging, 24:246-253, 2005.

Pan, D. Xia, L. Yu, and Y. Zou. A unified analysis of FBP-based reconstruction algorithms for circular cone- and fan-beam scans. Phys. Med. Biol., 49:4349-4369, 2004.

Zou Y, Pan X Exact image reconstruction on PI-line from minimum data in helical cone-beam CT Phys. Med. Biol. 49 941-59, 2004.

Zou Y, Pan X. Image reconstruction on PI-lines by use of filtered backprojection in helical cone-beam CT. Phys Med Biol. 49(12):2717-31, 2004 .

File Number: 1171 

IP Protection

Patent Number(s): 7444011, 7394923

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