Design of iterative ROI transmission tomography reconstruction procedures and image quality analysis

Hamelin, Benoit; Goussard, Yves; Dussault, Jean-Pièrre; Cloutier, Guy; Beaudoin, G.; Soulez, Gilles

doi:10.1118/1.3447722

Cited by 18 publications

(11 citation statements)

References 21 publications

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“…For each of these patches a different energy and resolution model could be defined. This is very similar to the region of interest reconstruction proposed by Hamelin et al 29,30 and Yu et al 31 In these papers, the approach was used to obtain a high resolution reconstruction in a small region of interest, in combination with a coarser (and faster) reconstruction of the surrounding background. Here, this approach was extended to implement a locally improved energy model and improved sampling of the detector elements.…”

Section: Discussionmentioning

confidence: 62%

Metal artifact reduction in computed tomography using local models in an image block‐iterative scheme

Slambrouck

Nuyts

2012

Medical Physics

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Purpose: In iterative reconstruction, metal artifacts can be reduced by applying more accurate reconstruction models that are usually also more computationally demanding. The hypothesis of this work is that these complex models only need to be applied in the vicinity of the metals and that a less complex model can be used for the remainder of the reconstruction volume.Method: A method is described that automatically divides the reconstruction volume into metal and nonmetal regions. The different regions are called patches. A different energy and resolution model can be assigned to each of the patches. The patches containing metals are reconstructed with a fully polychromatic spectral model (IMPACT) and if necessary with an increased resolution model. The patch without metals is reconstructed with a simple polychromatic model (MLTRC) that only includes the spectral behavior of water attenuation. Comparing the computational complexity of IMPACT and MLTRC gives a ratio of 8:3. The different patches are updated sequentially as in a grouped coordinate algorithm. Two phantoms were simulated and measured: a circular phantom containing small metal cylinders and a body phantom representing a human pelvis with two femoral implants. As a first test, the sequential update of the patches was applied while using the same energy model for all patches. Secondly, the local model approach was applied using MLTRC for non-metal regions and IMPACT for metal regions. The results of different iterative reconstruction schemes are compared to the results of projection completion, another important method for the reduction of metal artifacts.Results: Reconstruction schemes including the sequential update of the patches result in images with less streak artifacts compared to a regular reconstruction. The sequential update of each of the metal regions improves the relative convergence of the metals (edges and attenuation values) against the rest of the image, which leads to an improved artifact reduction. Using the combined IMPACT+MLTRC model results in a similar image quality as using IMPACT everywhere, while providing an important benefit regarding computational complexity. Some streak and shadow artifacts were still present, but all structures present in the phantom could be observed. Projection completion results in reconstructions with less obvious streak and shadow artifacts but tends to deform or erase structures lying close to or in between metallic structures. Conclusions:Metal artifact reduction with iterative reconstruction can be achieved by using complex models only locally without losing image quality. Separately updating metal regions leads to reduced streak artifacts. Structures lying close to or in between metals are often better reconstructed, compared to projection completion results, because all available information is used.

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Section: Discussionmentioning

confidence: 62%

Metal artifact reduction in computed tomography using local models in an image block‐iterative scheme

Slambrouck

Nuyts

2012

Medical Physics

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“…That kind of approach has already be shown to reduce memory usage and computation time significantly 7 but to increase image noise. 8 We showed that using our method also an image quality close to full FOV iterative reconstruction can be reached.…”

Section: Discussionmentioning

confidence: 89%

“…In the upcoming sections we will refer to this approach as method Z. Hamelin et al extended the ROI reconstruction using a coarse-grid penalized likelihood (PL) full FOV reconstruction for the background and a fine grid for the ROI. 6,8 They show that artefacts, like beam-hardening or streaking, in the analytical reconstruction used by method Z propagate to the later ROI reconstruction. Using a not-too-coarse image grid in combination with an edgepreserving PL reconstruction produced significantly better images than method Z.…”

Section: Introductionmentioning

confidence: 96%

Region of interest processing for iterative reconstruction in x-ray computed tomography

Kopp¹,

Nasirudin²,

Mei³

et al. 2015

SPIE Proceedings

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The recent advancements in the graphics card technology raised the performance of parallel computing and contributed to the introduction of iterative reconstruction methods for x-ray computed tomography in clinical CT scanners. Iterative maximum likelihood (ML) based reconstruction methods are known to reduce image noise and to improve the diagnostic quality of low-dose CT. However, iterative reconstruction of a region of interest (ROI), especially ML based, is challenging. But for some clinical procedures, like cardiac CT, only a ROI is needed for diagnostics. A high-resolution reconstruction of the full field of view (FOV) consumes unnecessary computation effort that results in a slower reconstruction than clinically acceptable. In this work, we present an extension and evaluation of an existing ROI processing algorithm. Especially improvements for the equalization between regions inside and outside of a ROI are proposed. The evaluation was done on data collected from a clinical CT scanner. The performance of the different algorithms is qualitatively and quantitatively assessed. Our solution to the ROI problem provides an increase in signal-to-noise ratio and leads to visually less noise in the final reconstruction. The reconstruction speed of our technique was observed to be comparable with other previous proposed techniques. The development of ROI processing algorithms in combination with iterative reconstruction will provide higher diagnostic quality in the near future.

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“…An additional step consisting of smoothing of the reprojected coarse grid line integrals was found to yield reduced noise in the ROI reconstruction (Rashed et al 2007). However, artifacts attributable to edge degradation and beam-hardening artifacts in the initial FBP were found in the iteratively reconstructed ROI obtained using this general approach (Hamelin et al 2010). …”

Section: Introductionmentioning

confidence: 99%

Multiresolution iterative reconstruction in high-resolution extremity cone-beam CT

et al. 2016

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Application of model-based iterative reconstruction (MBIR) to high resolution cone-beam CT (CBCT) is computationally challenging because of the very fine discretization (voxel size <100 µm) of the reconstructed volume. Moreover, standard MBIR techniques require that the complete transaxial support for the acquired projections is reconstructed, thus precluding acceleration by restricting the reconstruction to a region-of-interest. To reduce the computational burden of high resolution MBIR, we propose a multiresolution Penalized-Weighted Least Squares (PWLS) algorithm, where the volume is parameterized as a union of fine and coarse voxel grids as well as selective binning of detector pixels. We introduce a penalty function designed to regularize across the boundaries between the two grids. The algorithm was evaluated in simulation studies emulating an extremity CBCT system and in a physical study on a test-bench. Artifacts arising from the mismatched discretization of the fine and coarse sub-volumes were investigated. The fine grid region was parameterized using 0.15 mm voxels and the voxel size in the coarse grid region was varied by changing a downsampling factor. No significant artifacts were found in either of the regions for downsampling factors of up to 4×. For a typical extremities CBCT volume size, this downsampling corresponds to an acceleration of the reconstruction that is more than five times faster than a brute force solution that applies fine voxel parameterization to the entire volume. For certain configurations of the coarse and fine grid regions, in particular when the boundary between the regions does not cross high attenuation gradients, downsampling factors as high as 10× can be used without introducing artifacts, yielding a ~50× speedup in PWLS. The proposed multiresolution algorithm significantly reduces the computational burden of high resolution iterative CBCT reconstruction and can be extended to other applications of MBIR where computationally expensive, high-fidelity forward models are applied only to a sub-region of the field-of-view.

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Design of iterative ROI transmission tomography reconstruction procedures and image quality analysis

Cited by 18 publications

References 21 publications

Metal artifact reduction in computed tomography using local models in an image block‐iterative scheme

Metal artifact reduction in computed tomography using local models in an image block‐iterative scheme

Region of interest processing for iterative reconstruction in x-ray computed tomography

Multiresolution iterative reconstruction in high-resolution extremity cone-beam CT

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