Dynamic relaxation in algebraic reconstruction technique (ART) for breast tomosynthesis imaging

Oliveira, N.; Mota, Ana M.; Matela, Nuno; Janeiro, L.; Almeida, Pedro

doi:10.1016/j.cmpb.2016.05.001

Cited by 12 publications

(4 citation statements)

References 11 publications

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“…The ray sum can be described as line integrals that map a three‐dimensional (3D) object to the detector pixels. According to [19, 21], ray sums,

r_{i}

, and function values,

f_{j}

, are defined as follows:

\sum_{j = 1}^{N} a_{i j} f_{j} = r_{i}, i = 1, 2, \dots, M .

The complete set of measured ray sums, through all the projection images, can be expressed as

S M_{s}

. Here, S is defined as the total number of projections, and

M_{s}

is the number of detector pixels in a projection image

P_{θ}

.…”

Section: Methodsmentioning

confidence: 99%

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High‐quality X‐ray computed tomography reconstruction using projected and interpolated images

D.M.Bappy

Jeon

2019

IET Image Processing

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Recent advances in computation power have allowed computed tomography (CT) to utilise iterative reconstruction (IR) algorithms. The IR technique can handle noisy data and reconstructs optimal CT images from limited projected images. As of cyclic image processing, IR improves the quality of CT images. This approach requires a minimum number of projections to reconstruct an image; however, decreasing the number of projections to 90 can create artefacts and degrade reconstruction quality. To overcome this limitation, the optical flow technique can compute flow vectors between two consecutive projections to generate projected images between frames. Here, optical flow-based frame interpolation combined with the ordered subsetmodified iterative technique is proposed to reduce computation time, lower the number of projections, and increase reconstruction quality of CT images. The proposed technique can be used to reconstruct a CT image from 90 projections at 4 degree intervals between projection sequences. This approach produces a much better quality reconstruction compared to that produced by an analytical algorithm, which uses 360 projections. The inclusion of an ordered subset reconstructs CT images quickly by accelerating streaming architecture.

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“…The ray sum can be described as line integrals that map a three‐dimensional (3D) object to the detector pixels. According to [19, 21], ray sums,

r_{i}

, and function values,

f_{j}

, are defined as follows:

\sum_{j = 1}^{N} a_{i j} f_{j} = r_{i}, i = 1, 2, \dots, M .

The complete set of measured ray sums, through all the projection images, can be expressed as

S M_{s}

. Here, S is defined as the total number of projections, and

M_{s}

is the number of detector pixels in a projection image

P_{θ}

.…”

Section: Methodsmentioning

confidence: 99%

“…The ray sum can be described as line integrals that map a threedimensional (3D) object to the detector pixels. According to [19,21], ray sums, r i , and function values, f j , are defined as follows:…”

Section: Problem Formulationmentioning

confidence: 99%

High‐quality X‐ray computed tomography reconstruction using projected and interpolated images

D.M.Bappy

Jeon

2019

IET Image Processing

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show abstract

“…A line integral that maps 3D objects to the detector pixel is known as a ray sum. Ray sums

p_{i}

and function values

f_{j}

are described by (1) [33, 34]

\sum_{j = 1}^{N} a_{i j} f_{j} = p_{i}, i = 1, 2, \dots, M

…”

Section: Methodsmentioning

confidence: 99%

Modified simultaneous iterative reconstruction technique for fast, high‐quality CT reconstruction

D.M.Bappy

Jeon

2017

IET Image Processing

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“…Mainly, iterative and analytical image reconstruction methods are applied in medical imaging modalities such as the optoacoustic tomography (OAT) (or photoacoustic tomography (PAT)) (Paltauf et al, 2002;Wang et al, 2012), the optical tomography (OT) (Dekker, Battista, & Jordan, 2017;Klose & Hielscher, 1999), the diffuse optical tomography (DOT) (Üncü et al, 2017;Sevim et al, 2017;Mercan et al, 2017;Mercan et al, 2019), the computed tomography (CT) (Sidky et al, 2006;Biguri et al, 2017) and the digital breast tomosynthesis (DBT) (Oliveira et al, 2016;Polat & Yildirim, 2018;Polat et al, 2019a). The CT, developed by Hounsfield and Cormack in the 1970s (Nobel Media AB, 2014;Raju, 1999), enables three-dimensional (3D) images of the examined part of the body like the head, chest, and breast.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Analysis of Alpha-Parametric Set for the Calculation of Intersection Lengths of Radiological Ray Path in Siddon's Algorithm Used in 3D Image Reconstruction

Polat

2021

Journal of Advanced Research in Natural and Applied Sciences

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The Siddon algorithm is one of the radiological ray path (x-ray) calculation tools used in 3D image reconstruction in medical imaging. In the algorithm, a set of alpha-parametric values is computed containing the length and index values where the voxel array of the x-ray intersects the x-y-z axes. In the alpha-set creation section of the Siddon algorithm, the set elements are sorted from small to large, but some elements have been noticed to have the same value in simulations. These elements are used to calculate which voxels are hit by the ray along the radiological path and at what ratio, but it was recognized that some values of the set were zero, which means some rays did not intersect some voxels at all. This situation may lead to data loss in 3D image reconstructions in medical imaging such as digital breast tomosynthesis (DBT) and computed tomography (CT) especially for huge dimensions such as size up to 800×800×50. Considering the mentioned problems, in this study, the effect of using or eliminating the same repetitive values in the alpha parametric set of the Siddon algorithm on calculations was investigated. To prove our proposal, we performed 3D image reconstruction (lossless and lossy) of a synthetic phantom at a size of 100×100×50. Using special functions that do not take into account the duplicate values in the algorithm, excluding the duplicate values from the calculation solved the stated problems (lossless reconstruction). In this way, data loss that may occur in 3D image reconstruction was reduced since voxel indices and intersection lengths were matched correctly and meaningfully.

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Dynamic relaxation in algebraic reconstruction technique (ART) for breast tomosynthesis imaging

Cited by 12 publications

References 11 publications

High‐quality X‐ray computed tomography reconstruction using projected and interpolated images

High‐quality X‐ray computed tomography reconstruction using projected and interpolated images

Modified simultaneous iterative reconstruction technique for fast, high‐quality CT reconstruction

Comprehensive Analysis of Alpha-Parametric Set for the Calculation of Intersection Lengths of Radiological Ray Path in Siddon's Algorithm Used in 3D Image Reconstruction

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