PO-1687 Evaluation of the CT eFOV image distortion and the effect on VMAT plan dosimetry

2021 ◽  
Vol 161 ◽  
pp. S1414
Author(s):  
S. Savva ◽  
N. Piracha
Keyword(s):  
Image Distortion

No-Reference Image Quality Assessment Based on Multi-Order Gradients Statistics

2020 ◽  
Vol 64 (1) ◽  
pp. 10505-1-10505-16
Author(s):  
Yin Zhang ◽  
Xuehan Bai ◽  
Junhua Yan ◽  
Yongqi Xiao ◽  
C. R. Chatwin ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Assessment Method ◽  
Image Distortion ◽  
Image Feature ◽  
Reference Image ◽  
Gradient Magnitude ◽  
Distortion Type

Abstract A new blind image quality assessment method called No-Reference Image Quality Assessment Based on Multi-Order Gradients Statistics is proposed, which is aimed at solving the problem that the existing no-reference image quality assessment methods cannot determine the type of image distortion and that the quality evaluation has poor robustness for different types of distortion. In this article, an 18-dimensional image feature vector is constructed from gradient magnitude features, relative gradient orientation features, and relative gradient magnitude features over two scales and three orders on the basis of the relationship between multi-order gradient statistics and the type and degree of image distortion. The feature matrix and distortion types of known distorted images are used to train an AdaBoost_BP neural network to determine the image distortion type; the feature matrix and subjective scores of known distorted images are used to train an AdaBoost_BP neural network to determine the image distortion degree. A series of comparative experiments were carried out using Laboratory of Image and Video Engineering (LIVE), LIVE Multiply Distorted Image Quality, Tampere Image, and Optics Remote Sensing Image databases. Experimental results show that the proposed method has high distortion type judgment accuracy and that the quality score shows good subjective consistency and robustness for all types of distortion. The performance of the proposed method is not constricted to a particular database, and the proposed method has high operational efficiency.

Three Dimensional Video Imaging for Endoscopic Sinus Surgery and Diagnosis

1995 ◽  
Vol 9 (4) ◽  
pp. 197-202 ◽  
Author(s):  
Anthony J. Reino ◽  
William Lawson ◽  
Baxter J. Garcia ◽  
Robert J. Greenstein
Keyword(s):  
Endoscopic Sinus Surgery ◽  
Three Dimensional ◽  
Small Diameter ◽  
Image Distortion ◽  
Sinus Surgery ◽  
Depth Of Field ◽  
Visual Fatigue ◽  
Video Imaging ◽  
Video Cameras ◽  
Technological Advances

Technological advances in video imaging over the last decade have resulted in remarkable additions to the armamentarium of instrumentation for the otolaryngologist. The use of video cameras and computer generated imaging in the operating room and office is invaluable for documentation and teaching purposes. Despite the obvious advantages of these systems, problems are evident, the most serious of which include image distortion and inability to judge depth of field. For more than 6 decades 3D imaging has been neither technically nor commercially successful. Reasons include alignment difficulties and image distortion. The result is “visual fatigue,” usually in about 15 minutes. At its extreme, this may be characterized by headache, nausea, and even vomiting. In this study, we employed the first 3D video imager to electronically manipulate a single video source to produce 3D images; therefore, neither alignment nor image distortions were produced. Of interest to the clinical surgeon, “visual fatigue” does not seem to occur; however, with prolonged procedures (greater than 2 hours) there exists the potential for physical intolerance for some individuals. This is the first unit that is compatible with any rigid or flexible videoendoscopic system and the small diameter endoscopes available for endoscopic sinus surgery. Moreover, prerecorded 2D tapes may be viewed in 3D on an existing VCR. The 3D image seems to provide enhanced anatomic awareness with less image distortion. We have found this system to be optically superior to the 2D video imagers currently available.

Arthroscopic image distortion—part I: the effect of lens and viewing angles in a 2-dimensional in vitro model

2014 ◽  
Vol 24 (6) ◽  
pp. 2065-2071 ◽  
Author(s):  
Yuichi Hoshino ◽  
Benjamin B. Rothrauff ◽  
Daniel Hensler ◽  
Freddie H. Fu ◽  
Volker Musahl
Keyword(s):  
In Vitro Model ◽  
Image Distortion ◽  
Vitro Model

Body-Image Distortion and Dissatisfaction in University Students

1986 ◽  
Vol 63 (2) ◽  
pp. 907-911 ◽  
Author(s):  
Harriett M. Mable ◽  
William D. G. Balance ◽  
Richard J. Galgan
Keyword(s):  
Body Image ◽  
University Students ◽  
Sex Role ◽  
Body Image Dissatisfaction ◽  
Self Esteem ◽  
Image Distortion ◽  
Body Image Disturbance ◽  
Sex Role Orientation ◽  
Body Image Distortion ◽  
Personality Variables

The present study investigated body-image distortion and body-image dissatisfaction for a sample of 75 male and 75 female university students, in relation to personality variables implicated in the literature, such as sex-role orientation, self-esteem, locus of control, and depression. Women perceived their weight deviation from the norm at over 15% above their actual deviation, whereas men distorted less than 1%. In a multiple regression analysis, none of the personality measures correlated significantly with body-image distortion; however, sex of subject accounted for 25% of its variance. Body dissatisfaction was significantly associated with low self-esteem, externality, depression, and distortion. The relationship between body-image distortion and dissatisfaction, although significant, was surprisingly small Apparently, these two aspects of body-image disturbance represent quite distinct constructs.

Modeling the image distortion of echelle spectrographs with T&P changes

2009 ◽  
Author(s):  
Frank Grupp ◽  
ShaoMing Hu ◽  
Liang Wang
Keyword(s):  
Image Distortion
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