Evaluation of three-dimensional iterative image reconstruction in virtual monochromatic imaging at 40 kilo-electron volts: phantom and clinical studies to assess the image noise and image quality in comparison with other reconstruction techniques

Objective: The purpose of this study was to evaluate the image quality in virtual monochromatic imaging (VMI) at 40 kilo-electron volts (keV) with three-dimensional iterative image reconstruction (3D-IIR). Methods: A phantom study and clinical study (31 patients) were performed with dual-energy CT (DECT). VMI at 40 keV was obtained and the images were reconstructed using filtered back projection (FBP), 50% adaptive statistical iterative reconstruction (ASiR), and 3D-IIR. We conducted subjective and objective evaluations of the image quality with each reconstruction technique. Results: The image contrast-to-noise ratio and image noise in both the clinical and phantom studies were significantly better with 3D-IIR than with 50% ASiR, and with 50% ASiR than with FBP (all, p < 0.05). The standard deviation and noise power spectra of the reconstructed images decreased in the order of 3D-IIR to 50% ASiR to FBP, while the modulation transfer function was maintained across the three reconstruction techniques. In most subjective evaluations in the clinical study, the image quality was significantly better with 3D-IIR than with 50% ASiR, and with 50% ASiR than with FBP (all, p < 0.001). Regarding the diagnostic acceptability, all images using 3D-IIR were evaluated as being fully or probably acceptable. Conclusions: The quality of VMI at 40 keV is improved by 3D-IIR, which allows the image noise to be reduced and structural details to be maintained. Advances in knowledge: The improvement of the image quality of VMI at 40 keV by 3D-IIR may increase the subjective acceptance in the clinical setting.

Download Full-text

AN IMPROVED 3DRP PET IMAGE RECONSTRUCTION METHOD WITH REBINNED DIRECT IMAGE ESTIMATE

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237206000373 ◽

2006 ◽

Vol 18 (05) ◽

pp. 237-245

Author(s):

WEI-MIN JENG ◽

HSUAN-HUI WANG

Keyword(s):

Image Reconstruction ◽

Image Quality ◽

Three Dimensional ◽

Simulation Software ◽

Direct Image ◽

Projection Data ◽

Reconstruction Method ◽

Two Dimensional ◽

Dimensional Image

The quality of traditional two-dimensional image reconstruction for PET has been efficiently improved by three-dimensional image reconstruction, but the sensitivity of the data and the quality of the image are restricted by the limit of modality physics. In analytical image reconstruction algorithm, 3DRP method compensates the unmeasured events by forward projection based on the initial direct image estimate. However, the original 3DRP method merely depends on the parallel projections without taking into account the oblique projections. In our proposed 3DRP-SSRB method, we improve the first image estimate by incorporating the rebinned oblique data. SSRB method was used to perform the rebinning operation to make uses of the oblique projection data to improve the sensitivity information. And then project the improved image estimate forward and reconstruct the final image. Conflicting parameters of reconstructed image quality of 3DRP are experimented by simulated three-dimensional phantom study with regard to both system sensitivity and image quality factors. PET simulation software package was used to conduct the experiment along with the MATLAB software to evaluate the effectiveness of two-dimensional FBP, 3DRP, and our proposed 3DRP-SSRB methods. The result demonstrated its better image quality by having better mean squared error numbers in most of output image slices.

Download Full-text

Enhanced Three-Dimensional Color Conversion Based on Discrete Wavelet Transform

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.155-156.440 ◽

2012 ◽

Vol 155-156 ◽

pp. 440-444

Author(s):

He Yan ◽

Xiu Feng Wang

Keyword(s):

Information Technology ◽

Wavelet Transform ◽

Image Reconstruction ◽

Image Quality ◽

Image Compression ◽

High Performance ◽

Three Dimensional ◽

Discrete Wavelet ◽

Compression Algorithms ◽

Color Conversion

JPEG2000 algorithm has been developed based on the DWT techniques, which have shown how the results achieved in different areas in information technology can be applied to enhance the performance. Lossy image compression algorithms sacrifice perfect image reconstruction in favor of decreased storage requirements. Wavelets have become a popular technology for information redistribution for high-performance image compression algorithms. Lossy compression algorithms sacrifice perfect image reconstruction in favor of improved compression rates while minimizing image quality lossy.

Download Full-text

Impact of total variation regularized expectation maximization reconstruction on the image quality of 68Ga-PSMA PET: a phantom and patient study

British Journal of Radiology ◽

10.1259/bjr.20201356 ◽

2021 ◽

pp. 20201356

Author(s):

Feng-Jiao Yang ◽

Shu-Yue Ai ◽

Runze Wu ◽

Yang Lv ◽

Hui-Fang Xie ◽

...

Keyword(s):

Prostate Cancer ◽

Image Quality ◽

Total Variation ◽

Expectation Maximization ◽

Image Noise ◽

Psma Pet ◽

Pet Ct ◽

Digital Pet ◽

The Impact

Objectives: To investigate the impact of total variation regularized expectation maximization (TVREM) reconstruction on the image quality of 68Ga-PSMA-11 PET/CT using phantom and patient data. Methods: Images of a phantom with small hot sphere inserts and 20 prostate cancer patients were acquired with a digital PET/CT using list-mode and reconstructed with ordered subset expectation maximization (OSEM) and TVREM with seven penalisation factors between 0.01 and 0.42 for 2 and 3 minutes-per-bed (m/b) acquisition. The contrast recovery (CR) and background variability (BV) of the phantom, image noise of the liver, and SUVmax of the lesions were measured. Qualitative image quality was scored by two radiologists using a 5-point scale (1-poor, 5-excellent). Results: The performance of CR, BV, and image noise, and the gain of SUVmax was higher for TVREM 2 m/b groups with the penalization of 0.07 to 0.28 compared to OSEM 3 m/b group (all p < 0.05). The image noise of OSEM 3 m/b group was equivalent to TVREM 2 and 3 m/b groups with a penalization of 0.14 and 0.07, while lesions’ SUVmax increased 15 and 20%. The highest qualitative score was attained at the penalization of 0.21 (3.30 ± 0.66) for TVREM 2 m/b groups and the penalization 0.14 (3.80 ± 0.41) for 3 m/b group that equal to or greater than OSEM 3 m/b group (2.90 ± 0.45, p = 0.2 and p < 0.001). Conclusions: TVREM improves lesion contrast and reduces image noise, which allows shorter acquisition with preserved image quality for PSMA PET/CT. Advances in knowledge: TVREM reconstruction with optimized penalization factors can generate higher quality PSMA-PET images for prostate cancer diagnosis.

Download Full-text

Application of deep learning image reconstruction algorithm to improve image quality in CT angiography of children with Takayasu arteritis

Journal of X-Ray Science and Technology ◽

10.3233/xst-211033 ◽

2021 ◽

pp. 1-8

Author(s):

Jihang Sun ◽

Haoyan Li ◽

Haiyun Li ◽

Michelle Li ◽

Yingzi Gao ◽

...

Keyword(s):

Deep Learning ◽

Image Reconstruction ◽

Image Quality ◽

Ct Angiography ◽

Takayasu Arteritis ◽

Image Noise ◽

Diagnostic Confidence ◽

Ct Number ◽

Laboratory Test Results ◽

Significant Difference

BACKGROUND: The inflammatory indexes of children with Takayasu arteritis (TAK) usually tend to be normal immediately after treatment, therefore, CT angiography (CTA) has become an important method to evaluate the status of TAK and sometime is even more sensitive than laboratory test results. OBJECTIVE: To evaluate image quality improvement in CTA of children diagnosed with TAK using a deep learning image reconstruction (DLIR) in comparison to other image reconstruction algorithms. METHODS: hirty-two TAK patients (9.14±4.51 years old) underwent neck, chest and abdominal CTA using 100 kVp were enrolled. Images were reconstructed at 0.625 mm slice thickness using Filtered Back-Projection (FBP), 50%adaptive statistical iterative reconstruction-V (ASIR-V), 100%ASIR-V and DLIR with high setting (DLIR-H). CT number and standard deviation (SD) of the descending aorta and back muscle were measured and contrast-to-noise ratio (CNR) for aorta was calculated. The vessel visualization, overall image noise and diagnostic confidence were evaluated using a 5-point scale (5, excellent; 3, acceptable) by 2 observers. RESULTS: There was no significant difference in CT number across images reconstructed using different algorithms. Image noise values (in HU) were 31.36±6.01, 24.96±4.69, 18.46±3.91 and 15.58±3.65, and CNR values for aorta were 11.93±2.12, 15.66±2.37, 22.54±3.34 and 24.02±4.55 using FBP, 50%ASIR-V, 100%ASIR-V and DLIR-H, respectively. The 100%ASIR-V and DLIR-H images had similar noise and CNR (all P > 0.05), and both had lower noise and higher CNR than FBP and 50%ASIR-V images (all P < 0.05). The subjective evaluation suggested that all images were diagnostic for large arteries, however, only 50%ASIR-V and DLIR-H met the diagnostic requirement for small arteries (3.03±0.18 and 3.53±0.51). CONCLUSION: DLIR-H improves CTA image quality and diagnostic confidence for TAK patients compared with 50%ASIR-V, and best balances image noise and spatial resolution compared with 100%ASIR-V.

Download Full-text

Improvement of Image Quality of Cone-beam CT Images by Three-dimensional Generative Adversarial Network

10.1109/embc46164.2021.9629952 ◽

2021 ◽

Author(s):

Takumi Hase ◽

Megumi Nakao ◽

Keiho Imanishi ◽

Mitsuhiro Nakamura ◽

Tetsuya Matsuda

Keyword(s):

Image Quality ◽

Cone Beam Ct ◽

Three Dimensional ◽

Ct Images ◽

Cone Beam ◽

Generative Adversarial Network ◽

Adversarial Network

Download Full-text

Validation of the CT iterative reconstruction technique for low-dose CT attenuation correction for improving the quality of PET images in an obesity-simulating body phantom and clinical study

Nuclear Medicine Communications ◽

10.1097/mnm.0000000000000326 ◽

2015 ◽

Vol 36 (8) ◽

pp. 839-847 ◽

Cited By ~ 1

Author(s):

Norikazu Matsutomo ◽

Akio Nagaki ◽

Masayuki Sasaki

Keyword(s):

Clinical Study ◽

Attenuation Correction ◽

Iterative Reconstruction ◽

Low Dose ◽

Reconstruction Technique ◽

Low Dose Ct ◽

Ct Attenuation ◽

Iterative Reconstruction Technique

Download Full-text

Evaluation of three-dimensional iterative image reconstruction in C-arm-based interventional cone-beam CT

Medicine ◽

10.1097/md.0000000000014947 ◽

2019 ◽

Vol 98 (13) ◽

pp. e14947

Author(s):

Shigeru Suzuki ◽

Yoshiaki Katada ◽

Tomoko Takayanagi ◽

Haruto Sugawara ◽

Takuya Ishikawa ◽

...

Keyword(s):

Image Reconstruction ◽

Cone Beam Ct ◽

Three Dimensional ◽

Cone Beam ◽

Iterative Image Reconstruction

Download Full-text

A modified discrete tomography for improving the reconstruction of unknown multi-gray-level material in the `missing wedge' situation

Journal of Synchrotron Radiation ◽

10.1107/s1600577518013681 ◽

2018 ◽

Vol 25 (6) ◽

pp. 1847-1859 ◽

Cited By ~ 1

Author(s):

Jianhong Liu ◽

Zhiting Liang ◽

Yong Guan ◽

Wenbin Wei ◽

Haobo Bai ◽

...

Keyword(s):

Three Dimensional ◽

Iteration Process ◽

Reconstruction Technique ◽

Morphological Operations ◽

Algebraic Reconstruction Technique ◽

Discrete Tomography ◽

Boundary Extraction ◽

X Ray ◽

Dimensional Reconstruction

Full angular rotational projections cannot always be acquired in tomographic reconstructions because of the limited space in the experimental setup, leading to the `missing wedge' situation. In this paper, a recovering `missing wedge' discrete algebraic reconstruction technique algorithm (rmwDART) has been proposed to solve the `missing wedge' problem and improve the quality of the three-dimensional reconstruction without prior knowledge of the material component's number or the material's values. By using oversegmentation, boundary extraction and mathematical morphological operations, `missing wedge' artifact areas can be located. Then, in the iteration process, by updating the located areas and regions, high-quality reconstructions can be obtained from the simulations, and the reconstructed images based on the rmwDART algorithm can be obtained from soft X-ray nano-computed tomography experiments. The results showed that there is the potential for discrete tomography.

Download Full-text