Optimization of a coded aperture coherent scatter spectral imaging system for medical imaging

Greenberg, Joel A.; Lakshmanan, Manu N.; Brady, David J.; Kapadia, Anuj J.

doi:10.1117/12.2082110

Cited by 15 publications

(18 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We consider an application of the proposed regularization scheme to a compressive fan beam system with energysensitive detectors, which has previously been described and characterized by Greenberg et al [10], [11]. The system consists of a 125 kvP X-ray source which has been collimated down to a small fan.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Spectrally grouped total variation reconstruction for scatter imaging using ADMM

Odinaka

Kaganovsky

Greenberg

et al. 2015

2015 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

Self Cite

View full text Add to dashboard Cite

Abstract-We consider X-ray coherent scatter imaging, where the goal is to reconstruct momentum transfer profiles (spectral distributions) at each spatial location from multiplexed measurements of scatter. Each material is characterized by a unique momentum transfer profile (MTP) which can be used to discriminate between different materials. We propose an iterative image reconstruction algorithm based on a Poisson noise model that can account for photon-limited measurements as well as various second order statistics of the data. To improve image quality, previous approaches use edge-preserving regularizers to promote piecewise constancy of the image in the spatial domain while treating each spectral bin separately. Instead, we propose spectrally grouped regularization that promotes piecewise constant images along the spatial directions but also ensures that the MTPs of neighboring spatial bins are similar, if they contain the same material. We demonstrate that this group regularization results in improvement of both spectral and spatial image quality. We pursue an optimization transfer approach where convex decompositions are used to lift the problem such that all hypervoxels can be updated in parallel and in closed-form. The group penalty introduces a challenge since it is not directly amendable to these decompositions. We use the alternating directions method of multipliers (ADMM) to replace the original problem with an equivalent sequence of sub-problems that are amendable to convex decompositions, leading to a highly parallel algorithm. We demonstrate the performance on real data.

show abstract

Section: Resultsmentioning

confidence: 99%

“…The array has 128 pixels and 64 energy channels. The rays leaving the object volume are incident on a coded aperture [13], [11], which allows for multiplexed measurement without the need for a rotating gantry.…”

Section: Resultsmentioning

confidence: 99%

Spectrally grouped total variation reconstruction for scatter imaging using ADMM

Odinaka

Kaganovsky

Greenberg

et al. 2015

2015 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

Self Cite

View full text Add to dashboard Cite

show abstract

“…The resolution could be improved further. The use of a coded aperture with finer features or greater spatial frequency would improve this spatial resolution, 24 especially at the boundaries of the sample, which are the most important regions of the specimen for the surgical margin application. In addition, acquiring additional projection data at a second view that is 90 degrees from the original view would also improve the spatial resolution along the z direction.…”

Section: Discussionmentioning

confidence: 99%

Coded aperture coherent scatter imaging for breast cancer detection: a Monte Carlo evaluation

et al. 2016

Self Cite

View full text Add to dashboard Cite

It is known that conventional x-ray imaging provides a maximum contrast between cancerous and healthy fibroglandular breast tissues of 3% based on their linear x-ray attenuation coefficients at 17.5 keV, whereas coherent scatter signal provides a maximum contrast of 19% based on their differential coherent scatter cross sections. Therefore in order to exploit this potential contrast, we seek to evaluate the performance of a codedaperture coherent scatter imaging system for breast cancer detection and investigate its accuracy using Monte Carlo simulations. In the simulations we modeled our experimental system, which consists of a raster-scanned pencil beam of x-rays, a bismuth-tin coded aperture mask comprised of a repeating slit pattern with 2-mm periodicity, and a linear-array of 128 detector pixels with 6.5-keV energy resolution. The breast tissue that was scanned comprised a 3-cm sample taken from a patient-based XCAT breast phantom containing a tomosynthesisbased realistic simulated lesion. The differential coherent scatter cross section was reconstructed at each pixel in the image using an iterative reconstruction algorithm. Each pixel in the reconstructed image was then classified as being either air or the type of breast tissue with which its normalized reconstructed differential coherent scatter cross section had the highest correlation coefficient.Comparison of the final tissue classification results with the ground truth image showed that the coded aperture imaging technique has a cancerous pixel detection sensitivity (correct identification of cancerous pixels), specificity (correctly ruling out healthy pixels as not being cancer) and accuracy of 92.4%, 91.9% and 92.0%, respectively. Our Monte Carlo evaluation of our experimental coded aperture coherent scatter imaging system shows that it is able to exploit the greater contrast available from coherently scattered x-rays to increase the accuracy of detecting cancerous regions within the breast.

show abstract

“…2, the extent along the z-direction is larger for the classified object than the ground truth, which is due to the limited spatial resolution achieved by the coded aperture. The use of a coded aperture with finer features or greater spatial frequency would improve this spatial resolution, 16 especially at the boundaries of the sample, which are the most important regions of the specimen for the surgical margin application. In addition, acquiring additional projection data at a second view that is 90 deg from the original view would also improve the spatial resolution along the z direction.…”

Section: Future Improvements To Spatial Resolution and Scan Durationmentioning

confidence: 99%

“…Coded aperture coherent scatter spectral imaging, which has been used for material-identification in nonmedical 15,16 and medical [17][18][19] applications, uses a coded aperture placed in front of the detector to make multiplexed measurements of the scatter. When the coded aperture is placed in front of the x-ray detector, it spatially modulates the scattered x-rays by a frequency dependent on the location of the scatter origin.…”

Section: Introductionmentioning

confidence: 99%

Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples

et al. 2016

Self Cite

View full text Add to dashboard Cite

Abstract. A scatter imaging technique for the differentiation of cancerous and healthy breast tissue in a heterogeneous sample is introduced in this work. Such a technique has potential utility in intraoperative margin assessment during lumpectomy procedures. In this work, we investigate the feasibility of the imaging method for tumor classification using Monte Carlo simulations and physical experiments. The coded aperture coherent scatter spectral imaging technique was used to reconstruct three-dimensional (3-D) images of breast tissue samples acquired through a single-position snapshot acquisition, without rotation as is required in coherent scatter computed tomography. We perform a quantitative assessment of the accuracy of the cancerous voxel classification using Monte Carlo simulations of the imaging system; describe our experimental implementation of coded aperture scatter imaging; show the reconstructed images of the breast tissue samples; and present segmentations of the 3-D images in order to identify the cancerous and healthy tissue in the samples. From the Monte Carlo simulations, we find that coded aperture scatter imaging is able to reconstruct images of the samples and identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) inside them with a cancerous voxel identification sensitivity, specificity, and accuracy of 92.4%, 91.9%, and 92.0%, respectively. From the experimental results, we find that the technique is able to identify cancerous and healthy tissue samples and reconstruct differential coherent scatter cross sections that are highly correlated with those measured by other groups using x-ray diffraction. Coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue inside samples within a time on the order of a minute per slice.

show abstract

Optimization of a coded aperture coherent scatter spectral imaging system for medical imaging

Cited by 15 publications

References 9 publications

Spectrally grouped total variation reconstruction for scatter imaging using ADMM

Spectrally grouped total variation reconstruction for scatter imaging using ADMM

Coded aperture coherent scatter imaging for breast cancer detection: a Monte Carlo evaluation

Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples

Contact Info

Product

Resources

About