scholarly journals Efficient Strike Artifact Reduction Based on 3D-Morphological Structure Operators from Filtered Back-Projection PET Images

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7228
Author(s):  
Chun-Yi Chiu ◽  
Yung-Hui Huang ◽  
Wei-Chang Du ◽  
Chi-Yuan Wang ◽  
Huei-Yong Chen ◽  
...  
Keyword(s):  
Image Quality ◽  
Three Dimensional ◽  
Morphological Structure ◽  
Whole Body ◽  
Noise Distribution ◽  
Parallel Operation ◽  
Back Projection ◽  
Nuclear Medicine Imaging ◽  
Filtered Back Projection ◽  
Reconstruction Methods

Positron emission tomography (PET) can provide functional images and identify abnormal metabolic regions of the whole-body to effectively detect tumor presence and distribution. The filtered back-projection (FBP) algorithm is one of the most common images reconstruction methods. However, it will generate strike artifacts on the reconstructed image and affect the clinical diagnosis of lesions. Past studies have shown reduction in strike artifacts and improvement in quality of images by two-dimensional morphological structure operators (2D-MSO). The morphological structure method merely processes the noise distribution of 2D space and never considers the noise distribution of 3D space. This study was designed to develop three-dimensional-morphological structure operators (3D MSO) for nuclear medicine imaging and effectively eliminating strike artifacts without reducing image quality. A parallel operation was also used to calculate the minimum background standard deviation of the images for three-dimensional morphological structure operators with the optimal response curve (3D-MSO/ORC). As a result of Jaszczak phantom and rat verification, 3D-MSO/ORC showed better denoising performance and image quality than the 2D-MSO method. Thus, 3D MSO/ORC with a 3 × 3 × 3 mask can reduce noise efficiently and provide stability in FBP images.

Three-dimensional Density Reconstruction Analysis Method for Omni-directional Muography

2020 ◽  
Author(s):  
Seigo Miyamoto ◽  
Shogo Nagahara
Keyword(s):  
Spatial Resolution ◽  
Three Dimensional ◽  
Cosmic Ray ◽  
Inversion Method ◽  
Density Structure ◽  
Back Projection ◽  
Analysis Method ◽  
Filtered Back Projection ◽  
Linear Inversion ◽  
Reconstruction Methods

<p>Muography is the technique to observe the inner density structure of volcano by using cosmic-ray muons. In previous study, three-dimensional density reconstruction was attempted by using muography data from multiple directions (Tanaka et al., 2010, Rosas-Carbajal et al., 2017), but they could only get a few hundred meters of spatial resolution. To improve the spatial resolution, Nagahara and Miyamoto (2018) suggested omni-directional muography, putting ten or more observation points to surround the volcano.</p><p>  There are two types of three-dimensional density reconstruction methods from omni-directional muography observations, the linear inversion method (Rosas-Carbajal et al., 2017) and the filtered back projection (FBP) method (Nagahara and Miyamoto, 2018). The former is applicable even when the number of observation points is small, but requires many arbitrary parameters, while the latter has the characteristic that no arbitrary parameters are required but a certain number of observation points is required.</p><p>In this presentation, we show the results of a comparison between the two methods in simulation.</p>

Image quality and radiation dose of CT venography with double dose reduction using model based iterative reconstruction: comparison with conventional CT venography using filtered back projection

2017 ◽  
Vol 59 (5) ◽  
pp. 546-552 ◽  
Author(s):  
Yeo-Jin Jeong ◽  
Ki Seok Choo ◽  
Kyung Jin Nam ◽  
Ji Won Lee ◽  
Jin You Kim ◽  
...  
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Iterative Reconstruction ◽  
Radiation Doses ◽  
Back Projection ◽  
Filtered Back Projection ◽  
Ct Venography ◽  
Group A ◽  
Vascular Enhancement ◽  
Group B

Background Computed tomography venography (CTV) at low kVp using model-based iterative reconstruction (MBIR) can enhance vascular enhancement with noise reduction. Purpose To evaluate image qualities and radiation doses of CTV at 80 kVp using MBIR and a small iodine contrast media (CM) dose and to compare these with those of CTV performed using a conventional protocol. Material and Methods Sixty-five patients (mean age = 58.1 ± 7.2 years) that underwent CTV for the evaluation of deep vein thrombosis (DVT) and varicose veins were enrolled in this study. Patients were divided into two groups: Group A (35 patients, 80 kVp, MBIR, automatic tube current modulation, CM = 270 mg/mL, 100 mL) and Group B (30 patients, 100 kVp, filtered back projection [FBP], 120 fixed mA, CM = 370 mg/mL, 120 mL). Objective and subjective image qualities of inferior vena cava (IVC), femoral vein (FV), and popliteal vein (PV) were assessed and radiation doses were recorded. Results Mean vascular enhancement in group A was significantly lower than in group B ( P < 0.01). Noise in group A was significantly lower than in group B except for PV and contrast-to-noise ratio were not significantly different in the two groups ( P > 0.05). In addition, radiation dose in group A was significantly lower than in group B ( P < 0.001). Subjective image quality comparison revealed group A was statistically inferior to group B except for subjective image noise. Conclusion CTV at 80 kVp using MBIR with small iodine contrast dose provided acceptable image quality at a lower radiation dose than conventional CTV using FBP.

scholarly journals Can a penalized-likelihood estimation algorithm be used to reduce the injected dose or the acquisition time in 68Ga-DOTATATE PET/CT studies?

2020 ◽  
Author(s):  
Alexandre Chicheportiche ◽  
Elinor Goshen ◽  
Jeremy Godefroy ◽  
Simona Grozinsky-Glasberg ◽  
Kira Oleinikov ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Image Quality ◽  
Regularization Parameter ◽  
Penalized Likelihood ◽  
Likelihood Estimation ◽  
Whole Body ◽  
Acquisition Time ◽  
Clinical Images ◽  
Penalized Likelihood Estimation ◽  
Reconstruction Methods

Abstract Background: Image quality and quantitative accuracy of Positron Emission Tomography (PET) depend on several factors such as uptake time, scanner characteristics and image reconstruction methods. Ordered subset expectation maximization (OSEM) is considered the gold standard for image reconstruction. Penalized-likelihood estimation (PL) algorithms have been recently developed for PET reconstruction to improve quantitation accuracy while maintaining or even improving image quality. In PL algorithms a regularization parameter β controls the penalization of relative differences between neighboring pixels and determines image characteristics. In the present study, we aim to compare the performance of Q.Clear (PL algorithm, GE Healthcare) and OSEM (3 iterations, 8 subsets, 6 mm post-processing filter) for 68Ga-DOTATATE (68Ga-DOTA) PET studies, both visually and quantitatively.Thirty consecutive whole-body 68Ga-DOTA studies were included. The data were acquired in list mode and were reconstructed using 3D OSEM and Q.Clear with various values of β, and various acquisition times per bed position (bp), thus generating images with reduced injected dose (1.5 min/bp: β=300-1100; 1.0 min/bp: β=600-1400 and 0.5 min/bp: β=800-2200). An additional analysis adding β values up to 1500, 1700 and 300 for 1.5, 1.0 and 0.5 min/bp, respectively, was performed for a random sample of 8 studies. Evaluation was performed using a phantom and clinical data. Two experienced nuclear medicine physicians blinded to the variables assessed the image quality visually.Results: Clinical images reconstructed with Q.Clear, set at 1.5, 1.0 min/bp and 0.5 min/bp using β = 1100, 1300, 3000 respectively, resulted in images with noise equivalence to 3D OSEM (1.5 min/bp) with a mean increase in SUVmax of 14%, 13% and 4%, an increase in SNR of 30%, 24% and 10%, and in SBR of 13%, 13% and 2%, respectively. Visual assessment yielded similar results for β values of 1300-1500 and 1500-1700 for 1.5 and 1.0 min/bp, respectively although for 0.5 min/bp there was no significant improvement compared to OSEM. Conclusion: 68Ga-DOTA reconstructions with Q.Clear, 1.5 and 1.0 min/bp resulted in increased tumor SUVmax and in improved SNR and SBR at a similar level of noise compared to 3D OSEM. Q.Clear with β =1500-1700 enables one-third reduction of acquisition time or injected dose, with similar image quality compared to 3D OSEM.

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