scholarly journals Effect of attenuation correction on image quality in emission tomography

2017 ◽  
Author(s):  
N. V. Denisova ◽  
M. M. Ondar
Keyword(s):  
Image Quality ◽  
Attenuation Correction ◽  
Emission Tomography

scholarly journals Deep learning-based image quality improvement of 18F-fluorodeoxyglucose positron emission tomography: a retrospective observational study

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Junichi Tsuchiya ◽  
Kota Yokoyama ◽  
Ken Yamagiwa ◽  
Ryosuke Watanabe ◽  
Koichiro Kimura ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Emission Tomography ◽  
Gaussian Filter ◽  
Fluorodeoxyglucose Positron Emission Tomography ◽  
Tumor Delineation ◽  
Standardized Uptake Values ◽  
Positron Emission ◽  
Image Quality Improvement ◽  
Fluorodeoxyglucose Positron Emission

Abstract Background Deep learning (DL)-based image quality improvement is a novel technique based on convolutional neural networks. The aim of this study was to compare the clinical value of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) images obtained with the DL method with those obtained using a Gaussian filter. Methods Fifty patients with a mean age of 64.4 (range, 19–88) years who underwent 18F-FDG PET/CT between April 2019 and May 2019 were included in the study. PET images were obtained with the DL method in addition to conventional images reconstructed with three-dimensional time of flight-ordered subset expectation maximization and filtered with a Gaussian filter as a baseline for comparison. The reconstructed images were reviewed by two nuclear medicine physicians and scored from 1 (poor) to 5 (excellent) for tumor delineation, overall image quality, and image noise. For the semi-quantitative analysis, standardized uptake values in tumors and healthy tissues were compared between images obtained using the DL method and those obtained with a Gaussian filter. Results Images acquired using the DL method scored significantly higher for tumor delineation, overall image quality, and image noise compared to baseline (P < 0.001). The Fleiss’ kappa value for overall inter-reader agreement was 0.78. The standardized uptake values in tumor obtained by DL were significantly higher than those acquired using a Gaussian filter (P < 0.001). Conclusions Deep learning method improves the quality of PET images.

A study on the change in image quality before and after an attenuation correction with the use of a CT image in a SPECT/CT scan

2012 ◽  
Vol 61 (12) ◽  
pp. 2060-2067
Author(s):  
Yong-Soon Park ◽  
Woo-Hyun Kim ◽  
Dong-Oh Shim ◽  
Ho-Sung Kim ◽  
Woon-Kwan Chung ◽  
...  
Keyword(s):  
Image Quality ◽  
Ct Scan ◽  
Attenuation Correction ◽  
Ct Image ◽  
Before And After

A hybrid method of attenuation correction for positron emission tomography brain studies

1994 ◽  
Vol 21 (12) ◽  
pp. 1279-1284 ◽  
Author(s):  
Valentino Bettinardi ◽  
Maria Carla Gilardi ◽  
Serena Cargnel ◽  
Giovanna Rizzo ◽  
Mika Teräs ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Attenuation Correction ◽  
Hybrid Method ◽  
Emission Tomography ◽  
Positron Emission

scholarly journals Effect of Gamma-Ray Energy on Image Quality in Passive Gamma Emission Tomography of Spent Nuclear Fuel

2019 ◽  
Vol 66 (1) ◽  
pp. 487-496
Author(s):  
Camille Belanger-Champagne ◽  
Pauli Peura ◽  
Paula Eerola ◽  
Tapani Honkamaa ◽  
Timothy White ◽  
...  
Keyword(s):  
Image Quality ◽  
Nuclear Fuel ◽  
Spent Nuclear Fuel ◽  
Gamma Ray ◽  
Emission Tomography ◽  
Gamma Emission
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