scholarly journals Micro-CT yields high image quality in human fetal post-mortem imaging despite maceration

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ian Craig Simcock ◽  
Susan Cheng Shelmerdine ◽  
Dean Langan ◽  
Guy Anna ◽  
Neil James Sebire ◽  
...  
Keyword(s):  
Image Quality ◽  
Pregnancy Loss ◽  
Ct Imaging ◽  
Quality Score ◽  
Image Quality Score ◽  
Invasive Technique ◽  
Tissue Preparation ◽  
Post Mortem ◽  
Micro Ct ◽  
High Image Quality

Abstract Background Current clinical post-mortem imaging techniques do not provide sufficiently high-resolution imaging for smaller fetuses after pregnancy loss. Post-mortem micro-CT is a non-invasive technique that can deliver high diagnostic accuracy for these smaller fetuses. The purpose of the study is to identify the main predictors of image quality for human fetal post-mortem micro-CT imaging. Methods Human fetuses were imaged using micro-CT following potassium tri-iodide tissue preparation, and axial head and chest views were assessed for image quality on a Likert scale by two blinded radiologists. Simple and multivariable linear regression models were performed with demographic details, iodination, tissue maceration score and imaging parameters as predictor variables. Results 258 fetuses were assessed, with median weight 41.7 g (2.6–350 g) and mean gestational age 16 weeks (11–24 weeks). A high image quality score (> 6.5) was achieved in 95% of micro-CT studies, higher for the head (median = 9) than chest (median = 8.5) imaging. The strongest negative predictors of image quality were increasing maceration and body weight (p < 0.001), with number of projections being the best positive imaging predictor. Conclusions High micro-CT image quality score is achievable following early pregnancy loss despite fetal maceration, particularly in smaller fetuses where conventional autopsy may be particularly challenging. These findings will help establish clinical micro-CT imaging services, addressing the need for less invasive fetal autopsy methods.

scholarly journals Swept Source Optical Coherence Tomography Angiography for Contact Lens-Related Corneal Vascularization

2016 ◽  
Vol 2016 ◽  
pp. 1-3 ◽  
Author(s):  
Marcus Ang ◽  
Yijun Cai ◽  
Anna C. S. Tan
Keyword(s):  
Optical Coherence Tomography ◽  
Image Quality ◽  
Contact Lens ◽  
Optical Coherence Tomography Angiography ◽  
Quality Score ◽  
Image Quality Score ◽  
Optical Coherence ◽  
Swept Source ◽  
Corneal Vascularization ◽  
Significant Difference

Purpose. To describe a novel technique of adapting a swept-source optical coherence tomography angiography (OCTA) to image corneal vascularization.Methods. In this pilot cross-sectional study, we obtained 3 × 3 mm scans, where 100,000 A-scans are acquired per second with optical axial resolution of 8 μm and lateral resolution of 20 μm. This was performed with manual “XYZ” focus without the anterior segment lens, until the focus of the corneoscleral surface was clearly seen and the vessels of interest were in focus on the corresponding red-free image. En face scans were evaluated based on image quality score and repeatability.Results. We analyzed scans from 10 eyes (10 patients) with corneal vascularization secondary to contact lens use in 4 quadrants, with substantial repeatability of scans in all quadrants (mean image quality score 2.7 ± 0.7;κ=0.75). There was no significant difference in image quality scores comparing quadrants (superior temporal: 2.9 ± 0.6, superior nasal: 2.8 ± 0.4, inferior temporal: 2.5 ± 0.9, and inferior nasal: 2.4 ± 1.0;P=0.276) and able to differentiate deep and superficial corneal vascularization.Conclusion. This early clinical study suggests that the swept-source OCTA used may be useful for examining corneal vascularization, which may have potential for clinical applications such as detecting early limbal stem cell damage.

The microcirculation image quality score: Development and preliminary evaluation of a proposed approach to grading quality of image acquisition for bedside videomicroscopy

2013 ◽  
Vol 28 (6) ◽  
pp. 913-917 ◽  
Author(s):  
Michael J. Massey ◽  
Ethan LaRochelle ◽  
Gabriel Najarro ◽  
Adarsh Karmacharla ◽  
Ryan Arnold ◽  
...  
Keyword(s):  
Image Quality ◽  
Image Acquisition ◽  
Quality Score ◽  
Image Quality Score ◽  
Preliminary Evaluation

Modeling Image Quality Score Distribution Using Alpha Stable Model

2021 ◽  
Author(s):  
Yixuan Gao ◽  
Xiongkuo Min ◽  
Wenhan Zhu ◽  
Xiao-Ping Zhang ◽  
Guangtao Zhai
Keyword(s):  
Image Quality ◽  
Quality Score ◽  
Image Quality Score ◽  
Stable Model ◽  
Score Distribution

scholarly journals A study of using a deep learning image reconstruction to improve the image quality of extremely low-dose contrast-enhanced abdominal CT for patients with hepatic lesions

2020 ◽  
pp. 20201086
Author(s):  
Le Cao ◽  
Xiang Liu ◽  
Jianying Li ◽  
Tingting Qu ◽  
Lihong Chen ◽  
...  
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Low Dose ◽  
Quality Score ◽  
Image Noise ◽  
Image Quality Score ◽  
Diagnostic Confidence ◽  
Abdominal Ct ◽  
Contrast Enhanced ◽  
Hepatic Lesions

Objective: To investigate the feasibility of using deep learning image reconstruction (DLIR) to significantly reduce radiation dose and improve image quality in contrast-enhanced abdominal CT. Methods: This was a prospective study. 40 patients with hepatic lesions underwent abdominal CT using routine dose (120kV, noise index (NI) setting of 11 with automatic tube current modulation) in the arterial-phase (AP) and portal-phase (PP), and low dose (NI = 24) in the delayed-phase (DP). All images were reconstructed at 1.25 mm thickness using ASIR-V at 50% strength. In addition, images in DP were reconstructed using DLIR in high setting (DLIR-H). The CT value and standard deviation (SD) of hepatic parenchyma, spleen, paraspinal muscle and lesion were measured. The overall image quality includes subjective noise, sharpness, artifacts and diagnostic confidence were assessed by two radiologists blindly using a 5-point scale (1, unacceptable and 5, excellent). Dose between AP and DP was compared, and image quality among different reconstructions were compared using SPSS20.0. Results: Compared to AP, DP significantly reduced radiation dose by 76% (0.76 ± 0.09 mSv vs 3.18 ± 0.48 mSv), DLIR-H DP images had lower image noise (14.08 ± 2.89 HU vs 16.67 ± 3.74 HU, p < 0.001) but similar overall image quality score as the ASIR-V50% AP images (3.88 ± 0.34 vs 4.05 ± 0.44, p > 0.05). For the DP images, DLIR-H significantly reduced image noise in hepatic parenchyma, spleen, muscle and lesion to (14.77 ± 2.61 HU, 14.26 ± 2.67 HU, 14.08 ± 2.89 HU and 16.25 ± 4.42 HU) from (24.95 ± 4.32 HU, 25.42 ± 4.99 HU, 23.99 ± 5.26 HU and 27.01 ± 7.11) with ASIR-V50%, respectively (all p < 0.001) and improved image quality score (3.88 ± 0.34 vs 2.87 ± 0.53; p < 0.05). Conclusion: DLIR-H significantly reduces image noise and generates images with clinically acceptable quality and diagnostic confidence with 76% dose reduction. Advances in knowledge: (1) DLIR-H yielded a significantly lower image noise, higher CNR and higher overall image quality score and diagnostic confidence than the ASIR-V50% under low signal conditions. (2) Our study demonstrated that at 76% lower radiation dose, the DLIR-H DP images had similar overall image quality to the routine-dose ASIR-V50% AP images.

Progress In The Practical Application Of Automated Image Analysis To Tem Negatives

1977 ◽  
Vol 35 ◽  
pp. 214-217
Author(s):  
F. A. Heckman ◽  
E. Redman ◽  
J.E. Connolly
Keyword(s):  
Image Analysis ◽  
Image Quality ◽  
Exposure Time ◽  
Image Contrast ◽  
Automated Image Analysis ◽  
Practical Application ◽  
Factors Affecting ◽  
High Image Quality ◽  
Qualitative Evidence ◽  
Comprehensive Study

In our initial publication on this subject1) we reported results demonstrating that contrast is the most important factor in producing the high image quality required for reliable image analysis. We also listed the factors which enhance contrast in order of the experimentally determined magnitude of their effect. The two most powerful factors affecting image contrast attainable with sheet film are beam intensity and KV. At that time we had only qualitative evidence for the ranking of enhancing factors. Later we carried out the densitometric measurements which led to the results outlined below.Meaningful evaluations of the cause-effect relationships among the considerable number of variables in preparing EM negatives depend on doing things in a systematic way, varying only one parameter at a time. Unless otherwise noted, we adhered to the following procedure evolved during our comprehensive study:Philips EM-300; 30μ objective aperature; magnification 7000- 12000X, exposure time 1 second, anti-contamination device operating.

Ultralow Dose CT Imaging for Navigated Skull Base Surgery Using ASIR and MBIR-2D and 3D Image Quality

2014 ◽  
Vol 75 (S 02) ◽  
Author(s):  
Gerlig Widmann ◽  
P. Schullian ◽  
R. Hoermann ◽  
E. Gassner ◽  
H. Riechelmann ◽  
...  
Keyword(s):  
Image Quality ◽  
Skull Base ◽  
Skull Base Surgery ◽  
Ct Imaging ◽  
3D Image ◽  
Ultralow Dose ◽  
2D And 3D

Document Image Quality Assessment with Relaying Reference to Determine Minimum Readable Resolution for Compression

2020 ◽  
Vol 2020 (9) ◽  
pp. 323-1-323-8
Author(s):  
Litao Hu ◽  
Zhenhua Hu ◽  
Peter Bauer ◽  
Todd J. Harris ◽  
Jan P. Allebach
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Research Area ◽  
Input Image ◽  
Quality Score ◽  
Document Image ◽  
Digital Cameras ◽  
Active Research ◽  
Traditional Approaches

Image quality assessment has been a very active research area in the field of image processing, and there have been numerous methods proposed. However, most of the existing methods focus on digital images that only or mainly contain pictures or photos taken by digital cameras. Traditional approaches evaluate an input image as a whole and try to estimate a quality score for the image, in order to give viewers an idea of how “good” the image looks. In this paper, we mainly focus on the quality evaluation of contents of symbols like texts, bar-codes, QR-codes, lines, and hand-writings in target images. Estimating a quality score for this kind of information can be based on whether or not it is readable by a human, or recognizable by a decoder. Moreover, we mainly study the viewing quality of the scanned document of a printed image. For this purpose, we propose a novel image quality assessment algorithm that is able to determine the readability of a scanned document or regions in a scanned document. Experimental results on some testing images demonstrate the effectiveness of our method.

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