Exact Radon rebinning algorithm for the long object problem in helical cone-beam CT

Schaller, Stefan; Noo, Frédéric; Sauer, Frank; Tam, K. C.; Lauritsch, Guenter; Flohr, Thomas

doi:10.1109/42.870247

Cited by 77 publications

(46 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The combined rotational motion of the gantry and the patient axial translation result in a helical trajectory of the collimator focal point around the brain. Similar to helical SPECT proposed for long-object cone-beam imaging (4)(5)(6), pinhole imaging (7), and CT scans (8)(9)(10), helical triple-HCB scans demonstrated markedly improved axial sampling and showed no signs of axial artifacts in simulation and experiments (2,3).…”

mentioning

confidence: 73%

Combination of Converging Collimators for High-Sensitivity Brain SPECT

Ter-Antonyan¹,

Jaszczak²,

Greer³

et al. 2009

J Nucl Med

View full text Add to dashboard Cite

The objective of this study, which is related to human brain SPECT, was to increase the sensitivity of a triple-camera SPECT system and reduce statistical noise in reconstructed images using a combination of converging collimators. The reason for combining collimators is to ensure both high sensitivity and sufficient sampling without trading off spatial resolution. Methods: A highsensitivity half-cone-beam (HCB) collimator, designed specifically for brain imaging, was combined with other collimators and compared with conventional parallel-beam and fanbeam circular orbit acquisitions. For comparison, previously studied HCB collimation with a circle-and-helix data acquisition trajectory was also included in this study. Simulations of the Hoffman 3-dimensional brain phantom were performed to calculate the efficiencies of collimators and their combinations and to quantitatively evaluate reconstruction bias, statistical noise, and signalto-noise ratios in the reconstructed images. Experimental brain phantom data were also acquired and compared for different acquisition types. Finally, a patient brain scan was obtained with a combination of HCB and fanbeam collimators and compared with a triple-fanbeam circular orbit acquisition. Results: A combination of 2 HCB collimators and 1 fanbeam collimator, compared with a triple-fanbeam collimator, can increase the photon detection efficiency by 27% and by more than a factor of 2, compared with triple-parallel-hole collimation, with equal spatial resolution measured on the axis of rotation. Quantitative analysis of reconstruction bias and visual analysis of the images showed no signs of sampling artifacts. Reconstructed images in the simulations, experimental brain phantom, and patient brain scans showed improved quality with this collimator combination due to increased sensitivity and reduced noise. Lesion visibility was also improved, as confirmed by signal-to-noise ratios. Alternatively, triple-HCB circle-and-helix acquisition has also shown competitive results, with a slight disadvantage in axial sampling and implementation procedure. Conclusion: Combined HCB and fanbeam collimation is a promising approach for high-sensitivity brain SPECT.

show abstract

mentioning

confidence: 73%

Combination of Converging Collimators for High-Sensitivity Brain SPECT

Ter-Antonyan¹,

Jaszczak²,

Greer³

et al. 2009

J Nucl Med

View full text Add to dashboard Cite

show abstract

“…In 2000 Schaller, etc also proposed an exact solution (PHI-method) (Schaller et al, 2000c) to solve long-object problem. The main novelty of the PHI-method is the introduction of a virtual object f φ (x) for each value of the azimuthal angle φ in the image space, with each virtual object having the property of being equal to the real object f(x) in some ROI(Ωm).…”

Section: Phi-methods (2000)mentioning

confidence: 99%

Review of Recent Developments in Cone-Beam Ct Reconstruction Algorithms for Long-Object Problem

Zeng¹,

Chen²

2011

Image Anal Stereol

View full text Add to dashboard Cite

Long-object problem and short-object problem both deal with reconstruction problems with truncated conebeam CT projections acquired with a helical path. They have significantly less practical limitations than original exact cone-beam CT reconstruction algorithms which the cone-beam must cover the whole object. The short-object problem can be defined as reconstruction of the whole object having a finite support in the axial direction with helical scan extends a little bit above and below the object's support. However the longobject problem is to reconstruct the central region of interest (ROI) of a long object having an infinite support in the axial direction with helical scan extends a little a bit above and below the ROI. Although the short-object problem is more difficult to solve than the conventional exact reconstruction with non-truncated projections, the long-object problem presents greater challenge to researchers. Recently, with the great development of panel detector technology and computer technology, more and more researchers have been inspired to work on it. Because of great practical value of long-object algorithms, this paper focuses on the review and discussion of recent developments in long-object algorithms. All Long-object algorithms are classified as exact and approximate algorithms. After going briefly over the history of cone-beam algorithms, some novel cone-beam long-object algorithms are introduced, such as: Tam's algorithm, PImethod, PHI-method, etc. Then, the methods described are being compared and discussed.

show abstract

“…With the advent of multi-row detectors in CT scanners, these theories have been extensively exploited to yield exact multi slice reconstruction using helical trajectories [7,8,9,10]. With C-arms however (such a trajectory being unnatural) there have been other suggestions like a circle and a line [11], two orthogonal circles [6], etc.…”

Section: Introductionmentioning

confidence: 98%

“…Zeng et al [11] employed Smith's method for a circle and orthogonal line geometry that was suitable for SPECT imaging. Various methods have also been proposed in helical CT that solve the long object problem and deal with axial truncation [7,8,9,13]. Unfortunately, the application of exact reconstruction theory in C-arm reconstructions has been relatively unpopular.…”

Section: Introductionmentioning

confidence: 99%

Exact 3D cone-beam reconstruction from projections obtained over a wobble trajectory on a C-arm

Ramamurthi

Prince

Strobel

2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821)

View full text Add to dashboard Cite

We propose a source trajectory for cone-beam geometry that satisfies the conditions for exact 3D reconstruction in the largest sphere that remains non-truncated in the field of view of a given source detector combination. The source trajectory is a natural variation of the traditional circular source trajectory and is achieved by modulating the elevation of the source from the equatorial plane. We use a shift variant filtering approach in developing a filtered back-projection algorithm for robust, and computationally efficient volumetric reconstruction. The method is theoretically exact, and we show some results based upon simulation studies using a mathematical phantom.

show abstract

Exact Radon rebinning algorithm for the long object problem in helical cone-beam CT

Cited by 77 publications

References 28 publications

Combination of Converging Collimators for High-Sensitivity Brain SPECT

Combination of Converging Collimators for High-Sensitivity Brain SPECT

Review of Recent Developments in Cone-Beam Ct Reconstruction Algorithms for Long-Object Problem

Exact 3D cone-beam reconstruction from projections obtained over a wobble trajectory on a C-arm

Contact Info

Product

Resources

About