The reconstructed residual error: A novel segmentation evaluation measure for reconstructed images in tomography

Roelandts, Tom; Batenburg, Kees Joost; Dekker, Arnold J. den; Sijbers, Jan

doi:10.1016/j.cviu.2014.05.007

Cited by 11 publications

(11 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The reconstructed residual error (RRE) has been proposed as a local inconsistency indicator of the segmentation quality and consistency with respect to the projection data [28]. It relies on the fact that while the unsegmented image is generally a good solution to the tomographic problem, the segmented image is generally not anymore.…”

Section: Hybrid Tomography Oriented Segmentationmentioning

confidence: 99%

“…After segmentation, because inconsistencies have been introduced, most of the remaining error lies in the range of the operator. Thus it can be efficiently highlighted by reconstructing the residual between the reprojection of the segmented volume and the initial projections [28].…”

Section: Hybrid Tomography Oriented Segmentationmentioning

confidence: 99%

“…The unsegmented image resides in the solution space of the tomographic problem, while the segmented image usually does not anymore [28]. It presents inconsistencies, which can be measured with either the reprojection distance [4] or the projection stack inconsistency [34].…”

Section: Estimation Of the Segmentation Inconsistencies Using The Promentioning

confidence: 99%

“…It presents inconsistencies, which can be measured with either the reprojection distance [4] or the projection stack inconsistency [34]. For this reason, the reconstructed residual error (RRE) has been proposed as a local (in)consistency indicator [28]. Figure 3 shows an example of segmentation ( fig.…”

Section: Estimation Of the Segmentation Inconsistencies Using The Promentioning

confidence: 99%

“…where W † denotes the pseudo-inverse of the projection matrix. In practice, the projection matrix is too large to allow its pseudo-inverse to be computed explicitly, and W † is approximated by a reconstruction algorithm [28]. For the sake of keeping the computational complexity low, we use the FBP algorithm.…”

Section: Estimation Of the Segmentation Inconsistencies Using The Promentioning

confidence: 99%

See 4 more Smart Citations

A Data Consistent Variational Segmentation Approach Suitable for Real-time Tomography

Sarkissian

Viganò

Batenburg

2018

View full text Add to dashboard Cite

Computed Tomography (CT) is an imaging technique that allows to reconstruct volumetric information of the analyzed objects from their projections. The most popular reconstruction technique is the Filtered Back Projection (FBP). It has the advantage of being the fastest technique available, but also the disadvantage to require a high number of projections to retrieve good quality reconstructions. In this article we propose a segmentation method for tomographic volumes composed of few materials. Our method combines existing high-quality variational segmentation frameworks with the data consistency approach used in tomography and discrete tomography. We show that our algorithm performs well under high noise level and with moderately low number of projections, and that the data consistency significantly improves the segmentation, at the cost of only one FBP reconstruction and forward projection.

show abstract

Section: Hybrid Tomography Oriented Segmentationmentioning

confidence: 99%

Section: Hybrid Tomography Oriented Segmentationmentioning

confidence: 99%

Section: Estimation Of the Segmentation Inconsistencies Using The Promentioning

confidence: 99%

Section: Estimation Of the Segmentation Inconsistencies Using The Promentioning

confidence: 99%

Section: Estimation Of the Segmentation Inconsistencies Using The Promentioning

confidence: 99%

See 3 more Smart Citations

A Data Consistent Variational Segmentation Approach Suitable for Real-time Tomography

Sarkissian

Viganò

Batenburg

2018

View full text Add to dashboard Cite

show abstract

Tabu-DART: a dynamic update strategy for efficient discrete algebraic reconstruction

et al. 2022

Self Cite

View full text Add to dashboard Cite

In X-ray computed tomography, discrete tomography (DT) algorithms have been successful at reconstructing objects composed of only a few distinct materials. Many DT-based methods rely on a divide-and-conquer procedure to reconstruct the volume in parts, which improves their run-time and reconstruction quality. However, this procedure is based on static rules, which introduces redundant computation and diminishes the efficiency. In this work, we introduce an update strategy framework that allows for dynamic rules and increases control for divide-and-conquer methods for DT. We illustrate this framework by introducing Tabu-DART, which combines our proposed framework with the Discrete Algebraic Reconstruction Technique (DART). Through simulated and real data reconstruction experiments, we show that our approach yields similar or improved reconstruction quality compared to DART, with substantially lower computational complexity.

show abstract

Discrete tomography in an in vivo small animal bone study

et al. 2017

View full text Add to dashboard Cite

This study aimed at assessing the feasibility of a discrete algebraic reconstruction technique (DART) to be used in in vivo small animal bone studies. The advantage of discrete tomography is the possibility to reduce the amount of X-ray projection images, which makes scans faster and implies also a significant reduction of radiation dose, without compromising the reconstruction results. Bone studies are ideal for being performed with discrete tomography, due to the relatively small number of attenuation coefficients contained in the image [namely three: background (air), soft tissue and bone]. In this paper, a validation is made by comparing trabecular bone morphometric parameters calculated from images obtained by using DART and the commonly used standard filtered back-projection (FBP). Female rats were divided into an ovariectomized (OVX) and a sham-operated group. In vivo micro-CT scanning of the tibia was done at baseline and at 2, 4, 8 and 12 weeks after surgery. The cross-section images were reconstructed using first the full set of projection images and afterwards reducing them in number to a quarter and one-sixth (248, 62, 42 projection images, respectively). For both reconstruction methods, similar changes in morphometric parameters were observed over time: bone loss for OVX and bone growth for sham-operated rats, although for DART the actual values were systematically higher (bone volume fraction) or lower (structure model index) compared to FBP, depending on the morphometric parameter. The DART algorithm was, however, more robust when using fewer projection images, where the standard FBP reconstruction was more prone to noise, showing a significantly bigger deviation from the morphometric parameters obtained using all projection images. This study supports the use of DART as a potential alternative method to FBP in X-ray micro-CT animal studies, in particular, when the number of projections has to be drastically minimized, which directly reduces scanning time and dose.

show abstract

The reconstructed residual error: A novel segmentation evaluation measure for reconstructed images in tomography

Cited by 11 publications

References 18 publications

A Data Consistent Variational Segmentation Approach Suitable for Real-time Tomography

A Data Consistent Variational Segmentation Approach Suitable for Real-time Tomography

Tabu-DART: a dynamic update strategy for efficient discrete algebraic reconstruction

Discrete tomography in an in vivo small animal bone study

Contact Info

Product

Resources

About