Compressed Sensing for Fast Image Acquisition in Pulse-Echo Ultrasound

2012 ◽  
Vol 57 (SI-1 Track-B) ◽  
Author(s):  
M. F. Schiffner ◽  
T. Jansen ◽  
G. Schmitz
Keyword(s):  
Compressed Sensing ◽  
Image Acquisition ◽  
Pulse Echo ◽  
Fast Image Acquisition

scholarly journals Sonography of the Sacrotuberous Ligaments: Landmarks for Obtaining an Optimal Longitudinal Section

2019 ◽  
pp. 23-27
Author(s):  
A. M. Yurkovskiy ◽  
S. L. Achinovich ◽  
I. V. Nazarenko
Keyword(s):  
Image Acquisition ◽  
Longitudinal Axis ◽  
Longitudinal Section ◽  
Ischial Tuberosity ◽  
Sacrotuberous Ligament ◽  
Spinous Processes ◽  
Age Range ◽  
Fast Image Acquisition

Objective: to develop a landmark suitable for fast image acquisition of the sacroiliac ligament in the longitudinal section. Material and methods. The position of the longitudinal axis of the sacro-ligamentous ligaments relative to the line of the spinous processes on the sonograms of 36 patients (the age range was 27-80) and 33 cadavers (the age range was 50-75) has been determined. Results. The obtained data allow to trace the image of the sacrotuberous ligament in the longitudinal section quickly (using the ischial tuberosity as a landmark and orienting the scanning plane of the sensor at an angle of 19-25° according to the line of the spinous processes).

Research on Fabric Image Acquisition Based on Compressed Sensing

2014 ◽  
Vol 989-994 ◽  
pp. 3698-3701
Author(s):  
Ji Cheng Dong ◽  
Sheng Qi Guan ◽  
Long Long Chen
Keyword(s):  
Theoretical Analysis ◽  
Compressed Sensing ◽  
Textile Industry ◽  
Image Acquisition ◽  
Sampling Rate ◽  
Image Data ◽  
Sampling Theorem ◽  
High Quality ◽  
Shannon’S Sampling Theorem

Amount of data in collecting data of fabric image in the textile industry put forward a new challenge to sensor end. Compressed Sensing (CS) breaks limit of conventional Shannon’s sampling theorem, so we can reconstruct a signal in Sub-sampling rate. In addition, theoretical analysis tells us that collecting the fabric image data by CS method have a better advantage than collecting the general image data. Having reconstructed three fabric images and one general image by CS method, we can easily find that the former have a high quality of reconstruction.

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