X-Ray Scatter Correction on Soft Tissue Images for Portable Cone Beam CT

Soft tissue images from portable cone beam computed tomography (CBCT) scanners can be used for diagnosis and detection of tumor, cancer, intracerebral hemorrhage, and so forth. Due to large field of view, X-ray scattering which is the main cause of artifacts degrades image quality, such as cupping artifacts, CT number inaccuracy, and low contrast, especially on soft tissue images. In this work, we propose the X-ray scatter correction method for improving soft tissue images. The X-ray scatter correction scheme to estimate X-ray scatter signals is based on the deconvolution technique using the maximum likelihood estimation maximization (MLEM) method. The scatter kernels are obtained by simulating the PMMA sheet on the Monte Carlo simulation (MCS) software. In the experiment, we used the QRM phantom to quantitatively compare with fan-beam CT (FBCT) data in terms of CT number values, contrast to noise ratio, cupping artifacts, and low contrast detectability. Moreover, the PH3 angiography phantom was also used to mimic human soft tissues in the brain. The reconstructed images with our proposed scatter correction show significant improvement on image quality. Thus the proposed scatter correction technique has high potential to detect soft tissues in the brain.

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MULTICENTRE COMPARISON OF IMAGE QUALITY FOR LOW-CONTRAST OBJECTS AND MICROCATHETER TIPS IN X-RAY-GUIDED TREATMENT OF ARTERIOVENOUS MALFORMATION IN THE BRAIN

Radiation Protection Dosimetry ◽

10.1093/rpd/ncv481 ◽

2015 ◽

Vol 169 (1-4) ◽

pp. 325-330

Author(s):

I. Hernández-Girón ◽

J. E. M. Mourik ◽

M. L. Overvelde ◽

W. J. H. Veldkamp ◽

D. Zweers ◽

...

Keyword(s):

Image Quality ◽

Arteriovenous Malformation ◽

Low Contrast ◽

X Ray ◽

The Brain

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Truncation effect reduction for fast iterative reconstruction in cone-beam CT

10.21203/rs.3.rs-900212/v1 ◽

2021 ◽

Author(s):

Sorapong Aootaphao ◽

Saowapak Thongvigitmanee ◽

Puttisak Puttawibul ◽

Pairash Thajchayapong

Keyword(s):

Soft Tissue ◽

Image Quality ◽

Radiation Dose ◽

Iterative Reconstruction ◽

Human Head ◽

Tissue Imaging ◽

Cone Beam ◽

Percentage Error ◽

Effective Radiation Dose ◽

Low Contrast

Abstract Background: Iterative reconstruction for cone-beam computed tomography (CBCT) has been applied to improve image quality and reduce radiation dose. In a case where an object is larger than a flat panel detector, most CBCT images contain truncated data or incomplete projections, which degrade image quality. In this work, we propose the truncation effect reduction for fast iterative reconstruction in CBCT imaging inside the field of view (FOV).Methods: The volume matrix size of FOV and the height of projection images were extrapolated to a suitable size. These extended projections were reconstructed by fast iterative reconstruction. Moreover, a smoothing parameter for noise regularization in iterative reconstruction was also modified to reduce the accumulated error while processing. The proposed work was evaluated by image quality measurements and compared with the conventional filtered back projection (FBP) method. To validate the proposed method, we used a head phantom for evaluation and tested on real human head data. Results: In the experimental results, the reconstructed images from the head phantom can be enhanced apparently. In addition, fast iteration reconstruction can be run continuously while remaining the consistent mean-percentage-error (MPE) value with a large number of iterations. The CNR of the soft-tissue images was improved by the increased contrast and the decreased noise. Visualization of low contrast in the ventricle and soft-tissue images can be observed much clearer compared to those from FBP using the same effective radiation dose of 5 mGy. Conclusions: Our proposed work has satisfactory performance to reduce the truncation effect, especially inside the FOV with better image quality for soft-tissue imaging. The convergence of fast iterative reconstruction tends to be stable for many iterations.

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Using 100- instead of 120-kVp computed tomography to diagnose pulmonary embolism almost halves the radiation dose with preserved diagnostic quality

Acta Radiologica ◽

10.3109/02841850903505222 ◽

2010 ◽

Vol 51 (3) ◽

pp. 260-270 ◽

Cited By ~ 24

Author(s):

Peter Björkdahl ◽

Ulf Nyman

Keyword(s):

Computed Tomography ◽

Pulmonary Embolism ◽

Image Quality ◽

Radiation Dose ◽

Effective Dose ◽

Ct Number ◽

Subjective Image Quality ◽

Diagnostic Quality ◽

X Ray ◽

Tube Potential

Background: Concern has been raised regarding the mounting collective radiation doses from computed tomography (CT), increasing the risk of radiation-induced cancers in exposed populations. Purpose: To compare radiation dose and image quality in a chest phantom and in patients for the diagnosis of pulmonary embolism (PE) at 100 and 120 peak kilovoltage (kVp) using 16-multichannel detector computed tomography (MDCT). Material and Methods: A 20-ml syringe containing 12 mg I/ml was scanned in a chest phantom at 100/120 kVp and 25 milliampere seconds (mAs). Consecutive patients underwent 100 kVp ( n = 50) and 120 kVp ( n = 50) 16-MDCT using a “quality reference” effective mAs of 100, 300 mg I/kg, and a 12-s injection duration. Attenuation (CT number), image noise (1 standard deviation), and contrast-to-noise ratio (CNR; fresh clot = 70 HU) of the contrast medium syringe and pulmonary arteries were evaluated on 3-mm-thick slices. Subjective image quality was assessed. Computed tomography dose index (CTDIvol) and dose–length product (DLP) were presented by the CT software, and effective dose was estimated. Results: Mean values in the chest phantom and patients changed as follows when X-ray tube potential decreased from 120 to 100 kVp: attenuation +23% and +40%, noise +38% and +48%, CNR −6% and 0%, and CTDIvol −38% and −40%, respectively. Mean DLP and effective dose in the patients decreased by 42% and 45%, respectively. Subjective image quality was excellent or adequate in 49/48 patients at 100/120 kVp. No patient with a negative CT had any thromboembolism diagnosed during 3-month follow-up. Conclusion: By reducing X-ray tube potential from 120 to 100 kVp, while keeping all other scanning parameters unchanged, the radiation dose to the patient may be almost halved without deterioration of diagnostic quality, which may be of particular benefit in young individuals.

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X-ray scatter correction algorithm for cone beam CT imaging

Medical Physics ◽

10.1118/1.1711475 ◽

2004 ◽

Vol 31 (5) ◽

pp. 1195-1202 ◽

Cited By ~ 220

Author(s):

Ruola Ning ◽

Xiangyang Tang ◽

David Conover

Keyword(s):

Cone Beam Ct ◽

Scatter Correction ◽

Ct Imaging ◽

Cone Beam ◽

Correction Algorithm ◽

X Ray

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Patient-based low dose cone beam CT acquisition settings for prostate image-guided radiotherapy treatments on a Varian TrueBeam linear accelerator

British Journal of Radiology ◽

10.1259/bjr.20200412 ◽

2020 ◽

Vol 93 (1115) ◽

pp. 20200412

Author(s):

Maria Antonietta Piliero ◽

Margherita Casiraghi ◽

Davide Giovanni Bosetti ◽

Simona Cima ◽

Letizia Deantonio ◽

...

Keyword(s):

Prostate Cancer ◽

Image Quality ◽

Low Dose ◽

Cone Beam Ct ◽

Subjective Evaluation ◽

Cone Beam ◽

Low Contrast ◽

Image Guided Radiotherapy ◽

Image Guided ◽

Prostate Cancer Radiotherapy

Objective: To evaluate the performance of low dose cone beam CT (CBCT) acquisition protocols for image-guided radiotherapy of prostate cancer. Methods: CBCT images of patients undergoing prostate cancer radiotherapy were acquired with the settings currently used in our department and two low dose settings at 50% and 63% lower exposure. Four experienced radiation oncologists and two radiation therapy technologists graded the images on five image quality characteristics. The scores were analysed through Visual Grading Regression, using the acquisition settings and the patient size as covariates. Results: The low dose acquisition settings have no impact on the image quality for patients with body profile length at hip level below 100 cm. Conclusions: A reduction of about 60% of the dose is feasible for patients with size below 100 cm. The visibility of low contrast features can be compromised if using the low dose acquisition settings for patients with hip size above 100 cm. Advances in knowledge: Low dose CBCT acquisition protocols for the pelvis, based on subjective evaluation of patient images.

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Three-dimensional cone beam computed tomographic image reorientation using soft tissues as reference for facial asymmetry diagnosis

The Angle Orthodontist ◽

10.2319/112112-890.1 ◽

2013 ◽

Vol 84 (1) ◽

pp. 38-47 ◽

Cited By ~ 12

Author(s):

Jae-Kyu Lee ◽

Pil-Kyo Jung ◽

Cheol-Hyun Moon

Keyword(s):

Soft Tissue ◽

Soft Tissues ◽

Three Dimensional ◽

Facial Asymmetry ◽

Cone Beam ◽

Expert Group ◽

Computed Tomographic ◽

Asymmetry Analysis ◽

Cbct Image ◽

Facial Midline

ABSTRACT Objective: To investigate discrepancies in results of facial asymmetry analysis using different cone beam computed tomography (CBCT) image reorientation methods and the effectiveness of soft tissue as a reorientation reference for analysis of facial asymmetry. Materials and Methods: An asymmetric group of 30 patients with 4 mm or more of chin point (menton [Me]) deviation and a symmetric group of 30 patients with less than 4 mm of deviation of Me were chosen as study subjects. Three orientation methods were used to calculate and compare Me deviation values of the 60 subjects. Two methods used only skeletal landmarks for reference, and one method included the soft tissue landmarks around the eye. Preferences of an expert group for the facial midline as determined by each reorientation method were also examined. Results: The examinations showed significant discrepancies in Me deviation values between the three reorientation methods. The expert group showed the greatest preference for the facial midline reorientation method that incorporated soft tissue landmarks of the eye. Conclusions: These study findings suggest that the inclusion of soft tissue landmarks, especially those around the eyes, is effective for three-dimensional CBCT image reorientation for facial asymmetry analysis.

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TU-D-I-611-06: A Direct, Empirical Method for X-Ray Scatter Correction in Digital Radiography and Cone-Beam CT

Medical Physics ◽

10.1118/1.1998385 ◽

2005 ◽

Vol 32 (6Part16) ◽

pp. 2092-2093 ◽

Cited By ~ 1

Author(s):

J Siewerdsen ◽

B Bakhtiar ◽

D Moseley ◽

S Richard ◽

H Keller ◽

...

Keyword(s):

Digital Radiography ◽

Cone Beam Ct ◽

Scatter Correction ◽

Empirical Method ◽

Cone Beam ◽

X Ray

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TH-D-BRC-01: Improvement of Megavoltage Cone-Beam CT Image Quality Using a Low-Atomic Number X-Ray Target

Medical Physics ◽

10.1118/1.3182672 ◽

2009 ◽

Vol 36 (6Part28) ◽

pp. 2811-2811

Author(s):

J Robar ◽

R Kelly

Keyword(s):

Image Quality ◽

Atomic Number ◽

Cone Beam Ct ◽

Cone Beam ◽

Ct Image ◽

X Ray ◽

Megavoltage Cone Beam Ct ◽

Ct Image Quality

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

Electronics ◽

10.3390/electronics8090944 ◽

2019 ◽

Vol 8 (9) ◽

pp. 944 ◽

Cited By ~ 4

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.

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