TU-E-217BCD-02: An X-Ray Scatter Correction Method for Dedicated Breast Computed Tomography

2012 ◽  
Vol 39 (6Part24) ◽  
pp. 3914-3914 ◽  
Author(s):  
I Sechopoulos
Keyword(s):  
Computed Tomography ◽  
Scatter Correction ◽  
Correction Method ◽  
X Ray ◽  
Breast Computed Tomography

scholarly journals Quantitative Imaging of Gd Nanoparticles in Mice Using Benchtop Cone-Beam X-ray Fluorescence Computed Tomography System

2019 ◽  
Vol 20 (9) ◽  
pp. 2315 ◽  
Author(s):  
Siyuan Zhang ◽  
Liang Li ◽  
Jiayou Chen ◽  
Zhiqiang Chen ◽  
Wenli Zhang ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Spatial Information ◽  
Quantitative Imaging ◽  
Scatter Correction ◽  
Photon Counting ◽  
Correction Method ◽  
Cone Beam ◽  
X Ray ◽  
Photon Counting Detector

Nanoparticles (NPs) are currently under intensive research for their application in tumor diagnosis and therapy. X-ray fluorescence computed tomography (XFCT) is considered a promising non-invasive imaging technique to obtain the bio-distribution of nanoparticles which include high-Z elements (e.g., gadolinium (Gd) or gold (Au)). In the present work, a set of experiments with quantitative imaging of GdNPs in mice were performed using our benchtop XFCT device. GdNPs solution which consists of 20 mg/mL NaGdF4 was injected into a nude mouse and two tumor-bearing mice. Each mouse was then irradiated by a cone-beam X-ray source produced by a conventional X-ray tube and a linear-array photon counting detector with a single pinhole collimator was placed on one side of the beamline to record the intensity and spatial information of the X-ray fluorescent photons. The maximum likelihood iterative algorithm with scatter correction and attenuation correction method was applied for quantitative reconstruction of the XFCT images. The results show that the distribution of GdNPs in each target slice (containing liver, kidney or tumor) was well reconstructed and the concentration of GdNPs deposited in each organ was quantitatively estimated, which indicates that this benchtop XFCT system provides convenient tools for obtaining accurate concentration distribution of NPs injected into animals and has potential for imaging of nanoparticles in vivo.

scholarly journals A Deep Learning-Based Scatter Correction of Simulated X-ray Images

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 944 ◽  
Author(s):  
Heesin Lee ◽  
Joonwhoan Lee
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Imaging System ◽  
Scatter Correction ◽  
Similarity Index ◽  
Real Data ◽  
Correction Method ◽  
Training Data ◽  
X Ray ◽  
Scatter Reduction

X-ray scattering significantly limits image quality. Conventional strategies for scatter reduction based on physical equipment or measurements inevitably increase the dose to improve the image quality. In addition, scatter reduction based on a computational algorithm could take a large amount of time. We propose a deep learning-based scatter correction method, which adopts a convolutional neural network (CNN) for restoration of degraded images. Because it is hard to obtain real data from an X-ray imaging system for training the network, Monte Carlo (MC) simulation was performed to generate the training data. For simulating X-ray images of a human chest, a cone beam CT (CBCT) was designed and modeled as an example. Then, pairs of simulated images, which correspond to scattered and scatter-free images, respectively, were obtained from the model with different doses. The scatter components, calculated by taking the differences of the pairs, were used as targets to train the weight parameters of the CNN. Compared with the MC-based iterative method, the proposed one shows better results in projected images, with as much as 58.5% reduction in root-mean-square error (RMSE), and 18.1% and 3.4% increases in peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM), on average, respectively.

Scatter Correction Method by Temporal Primary Modulation in X-Ray CT

2012 ◽  
Vol 59 (6) ◽  
pp. 3278-3285 ◽  
Author(s):  
K. Schorner ◽  
M. Goldammer ◽  
K. Stierstorfer ◽  
J. Stephan ◽  
P. Boni
Keyword(s):  
Scatter Correction ◽  
Correction Method ◽  
X Ray

scholarly journals X-ray scatter correction for multi-source interior computed tomography

2017 ◽  
Vol 44 (1) ◽  
pp. 71-83 ◽  
Author(s):  
Hao Gong ◽  
Hao Yan ◽  
Xun Jia ◽  
Bin Li ◽  
Ge Wang ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Scatter Correction ◽  
X Ray

Scatter Correction in Cone-Beam Breast Computed Tomography: Simulations and Experiments

2012 ◽  
Vol 59 (5) ◽  
pp. 2008-2019 ◽  
Author(s):  
G. Mettivier ◽  
N. Lanconelli ◽  
S. L. Meo ◽  
P. Russo
Keyword(s):  
Computed Tomography ◽  
Scatter Correction ◽  
Cone Beam ◽  
Breast Computed Tomography

scholarly journals Scatter correction method for x-ray CT using primary modulation: Phantom studies

2010 ◽  
Vol 37 (2) ◽  
pp. 934-946 ◽  
Author(s):  
Hewei Gao ◽  
Rebecca Fahrig ◽  
N. Robert Bennett ◽  
Mingshan Sun ◽  
Josh Star-Lack ◽  
...  
Keyword(s):  
Scatter Correction ◽  
Correction Method ◽  
X Ray ◽  
Phantom Studies
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