scholarly journals A projection image database to investigate factors affecting image quality in weight-based dosing: application to pediatric renal SPECT

2018 ◽  
Vol 63 (14) ◽  
pp. 145004 ◽  
Author(s):  
Ye Li ◽  
Shannon O’Reilly ◽  
Donika Plyku ◽  
S Ted Treves ◽  
Yong Du ◽  
...  
Keyword(s):  
Image Quality ◽  
Image Database ◽  
Factors Affecting ◽  
Projection Image

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.

A clinical evaluation of some factors affecting image quality in panoramic radiography

1999 ◽  
Vol 29 (2) ◽  
pp. 81-84 ◽  
Author(s):  
G Kaeppler ◽  
D Axmann-Krcmar ◽  
I Reuter ◽  
J Meyle ◽  
G Gómez-Román
Keyword(s):  
Image Quality ◽  
Clinical Evaluation ◽  
Panoramic Radiography ◽  
Factors Affecting

Factors affecting image quality

Get Through ◽  
2020 ◽  
pp. 39-55
Author(s):  
Damian Tolan ◽  
Rachel Hyland ◽  
Christopher Taylor ◽  
Arnold Cowen
Keyword(s):  
Image Quality ◽  
Factors Affecting

Colourlab Image Database: Geometric Distortions

2021 ◽  
Vol 2021 (29) ◽  
pp. 258-263
Author(s):  
Marius Pedersen ◽  
Seyed Ali Amirshahi
Keyword(s):  
Image Quality ◽  
High Performance ◽  
Image Database ◽  
Quality Metrics ◽  
Current Image ◽  
Geometric Distortions ◽  
Image Quality Metrics ◽  
Objective Metrics ◽  
Reference Images

Over the years, a high number of different objective image quality metrics have been proposed. While some image quality metrics show a high correlation with subjective scores provided in different datasets, there still exists room for improvement. Different studies have pointed to evaluating the quality of images affected by geometrical distortions as a challenge for current image quality metrics. In this work, we introduce the Colourlab Image Database: Geometric Distortions (CID:GD) with 49 different reference images made specifically to evaluate image quality metrics. CID:GD is one of the first datasets which include three different types of geometrical distortions; seam carving, lens distortion, and image rotation. 35 state-ofthe-art image quality metrics are tested on this dataset, showing that apart from a handful of these objective metrics, most are not able to show a high performance. The dataset is available at <ext-link ext-link-type="url" xlink:href="http://www.colourlab.no/cid">www.colourlab.no/cid</ext-link>.

Factors affecting computed tomography image quality for assessment of mechanical aortic valves

2015 ◽  
Vol 32 (S1) ◽  
pp. 63-71 ◽  
Author(s):  
Young Joo Suh ◽  
Young Jin Kim ◽  
Yoo Jin Hong ◽  
Hye-Jeong Lee ◽  
Jin Hur ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Aortic Valves ◽  
Factors Affecting ◽  
Tomography Image ◽  
Computed Tomography Image

Comparison of Intra- and Postoperative 3-Dimensional Digital Subtraction Angiography in Evaluation of the Surgical Result After Intracranial Aneurysm Treatment

Neurosurgery ◽  
2019 ◽  
Vol 87 (4) ◽  
pp. 689-696 ◽  
Author(s):  
Serge Marbacher ◽  
Jenny C Kienzler ◽  
Itai Mendelowitsch ◽  
Donato D’Alonzo ◽  
Lukas Andereggen ◽  
...  
Keyword(s):  
Image Quality ◽  
Intracranial Aneurysm ◽  
Digital Subtraction Angiography ◽  
Three Dimensional ◽  
Standard Of Care ◽  
Digital Subtraction ◽  
Factors Affecting ◽  
Imaging Quality ◽  
3 Dimensional ◽  
Surgical Result

Abstract BACKGROUND Postoperative three-dimensional digital subtraction angiography (3D-DSA) is the gold standard in evaluating intracranial aneurysm (IA) remnants after clipping. Should intraoperative 3D-DSA image quality be equally good as postoperative 3D-DSA, it could supplant the latter as standard of care for follow-up of clipped IA. OBJECTIVE To directly compare the quality of assessment of clipped IA by intraoperative and postoperative 3D-DSA. METHODS From a prospective cohort of 221 consecutive patients who underwent craniotomy for IA treatment in a hybrid operating room, we retrospectively studied 26 patients who had both intraoperative and postoperative 3D-DSA imaging of their clipped aneurysm. Comparison of intraoperative and postoperative 3D-DSA images (blinded for review) included parameters that affected image quality and differences between the 2 periods. RESULTS In the 26 patients with 32 clipped IAs, the mean interval was 11 ± 7 mo between intraoperative and postoperative imaging 3D-DSA examinations. Reconstruction with multiple clips was used in 14 (44%) cases. Of 15 remnants, 9 (60%) were small (&lt;2 mm). In comparing intraoperative and postoperative 3D-DSA, no discordance or discrepancy in assessment of the surgical result was noted for any clipped IA, and overall imaging quality was excellent for both modalities. Factors affecting minor differences in image quality were not identified. CONCLUSION Compared with postoperative 3D-DSA, intraoperative 3D-DSA images achieved equally high quality and effective, immediate interpretation of the surgical clipping result. With comparable imaging quality and no discordant findings, intraoperative 3D-DSA could replace postoperative 3D-DSA to become the standard of care in IA surgery.

Anti-Forensics for Unsharp Masking Sharpening in Digital Images

2013 ◽  
Vol 5 (3) ◽  
pp. 53-65 ◽  
Author(s):  
Lu Laijie ◽  
Yang Gaobo ◽  
Xia Ming
Keyword(s):  
Performance Evaluation ◽  
Image Quality ◽  
Abrupt Change ◽  
Image Database ◽  
Image Editing ◽  
Detection Ability ◽  
Unsharp Masking ◽  
Passive Forensics ◽  
Adobe Photoshop ◽  
Image Edges

As a retouching tool, image sharpening can be applied as the final step to hide those possible forgery operations in an image. Unsharp masking (USM) is a popular sharpening method supported by most image editing software such as Adobe Photoshop. Several passive forensics methods have been presented for the detection of USM Sharpening. In this paper, an anti-forensic scheme for USM Sharpening is proposed to invalidate the existing forensic algorithms. It removes the overshoot artifacts in image edges and abrupt change in histogram ends. The effectiveness of the proposed method is proved by the experimental results on a large image database with various parameter settings. Comparisons are made among the unsharpened images, the sharpened images and the anti-forensic dithered image. Both the detection ability and image quality are used for its performance evaluation.

Color image database for evaluation of image quality metrics

2008 ◽  
Author(s):  
N. Ponomarenko ◽  
V. Lukin ◽  
K. Egiazarian ◽  
J. Astola ◽  
M. Carli ◽  
...  
Keyword(s):  
Image Quality ◽  
Color Image ◽  
Image Database ◽  
Quality Metrics ◽  
Image Quality Metrics

scholarly journals Image Quality Assessment without Reference by Combining Deep Learning-Based Features and Viewing Distance

2021 ◽  
Vol 11 (10) ◽  
pp. 4661
Author(s):  
Aladine Chetouani ◽  
Marius Pedersen
Keyword(s):  
Image Quality ◽  
Image Quality Assessment ◽  
Feature Vector ◽  
Pearson Correlation ◽  
Image Database ◽  
Viewing Distance ◽  
Quality Metric ◽  
Image Quality Metric ◽  
Fully Connected

An abundance of objective image quality metrics have been introduced in the literature. One important essential aspect that perceived image quality is dependent on is the viewing distance from the observer to the image. We introduce in this study a novel image quality metric able to estimate the quality of a given image without reference for different viewing distances between the image and the observer. We first select relevant patches from the image using saliency information. For each patch, a feature vector is extracted from a convolutional neural network model and concatenated at the viewing distance, for which the quality is predicted. The resulting vector is fed to fully connected layers to predict subjective scores for the considered viewing distance. The proposed method was evaluated using the Colourlab Image Database: Image Quality and Viewing Distance-changed Image Database. Both databases provide subjective scores at two different viewing distances. In the Colourlab Image Database: Image Quality we obtain a Pearson correlation of 0.87 at both 50 cm and 100 cm viewing distances, while in the Viewing Distance-changed Image Database we obtained a Pearson correlation of 0.93 and 0.94 at viewing distance of four and six times the image height. The results show the efficiency of our method and its generalization ability.

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