3D/4D sonography – any safety problem

2016 ◽  
Vol 44 (2) ◽  
Author(s):  
Ritsuko K. Pooh ◽  
Kazuo Maeda ◽  
Asim Kurjak ◽  
Cihat Sen ◽  
Alaa Ebrashy ◽  
...  
Keyword(s):  
Image Data ◽  
3D Ultrasound ◽  
Surface Rendering ◽  
Gray Scale ◽  
3D Images ◽  
Safety Problem ◽  
Short Intervals ◽  
Perpendicular Plane ◽  
4D Ultrasound ◽  
Gray Scale Image

AbstractGray-scale image data are processed in 3D ultrasound by repeated scans of multiple planes within a few seconds to achieve one surface rendering image and three perpendicular plane images. The 4D image is achieved by repeating 3D images in short intervals, i.e. 3D and 4D ultrasound are based on simple B-mode images. During 3D/4D acquisition, a fetus

scholarly journals Target tracking accuracy and latency with different 4D ultrasound systems – a robotic phantom study

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Svenja Ipsen ◽  
Sven Böttger ◽  
Holger Schwegmann ◽  
Floris Ernst
Keyword(s):  
Target Tracking ◽  
Real Time ◽  
Template Matching ◽  
Image Data ◽  
Distinct Advantage ◽  
Reference Trajectory ◽  
Data Streaming ◽  
Tracking Accuracy ◽  
Time Data ◽  
4D Ultrasound

AbstractUltrasound (US) imaging, in contrast to other image guidance techniques, offers the distinct advantage of providing volumetric image data in real-time (4D) without using ionizing radiation. The goal of this study was to perform the first quantitative comparison of three different 4D US systems with fast matrix array probes and real-time data streaming regarding their target tracking accuracy and system latency. Sinusoidal motion of varying amplitudes and frequencies was used to simulate breathing motion with a robotic arm and a static US phantom. US volumes and robot positions were acquired online and stored for retrospective analysis. A template matching approach was used for target localization in the US data. Target motion measured in US was compared to the reference trajectory performed by the robot to determine localization accuracy and system latency. Using the robotic setup, all investigated 4D US systems could detect a moving target with sub-millimeter accuracy. However, especially high system latency increased tracking errors substantially and should be compensated with prediction algorithms for respiratory motion compensation.

Application of image enhancement and pattern recognition algorithms to seismic reflection data

1983 ◽  
Vol 73 (1) ◽  
pp. 307-314
Author(s):  
George A. McMechan
Keyword(s):  
Pattern Recognition ◽  
Pacific Ocean ◽  
Image Enhancement ◽  
Seismic Reflection ◽  
Gray Scale ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Recognition Algorithms ◽  
Gray Scale Image ◽  
Northeastern Pacific

abstract A digital seismic reflection section may be converted to a gray scale image composed of pixels and processed with techniques borrowed from the disciplines of image enhancement and pattern recognition. Types of processing include scaling, thresholding, density equalization, filtering, segmentation, and edge-finding. These are successfully applied to a migrated common mid-point seismic reflection line that traverses the Queen Charlotte fault (located in the northeastern Pacific Ocean). The result is the definition and enhancement of an elongated, near-vertical reflectivity anomaly associated with the Queen Charlotte fault.

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