We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.
Features Partner Sites Information LinkXpress
Sign In
Advertise with Us
Ampronix,  Inc

Download Mobile App

Adding Color to Ultrasound Helps Differentiate Structures

By Daniel Beris
Posted on 15 Nov 2016
Print article
Image: An increase in fatty lipids in liver tissue is shown in blue using the H-scan format, compared to normal tissue (Photo courtesy of Professor Kevin Parker).
Image: An increase in fatty lipids in liver tissue is shown in blue using the H-scan format, compared to normal tissue (Photo courtesy of Professor Kevin Parker).
A new study describes how novel algorithms incorporate color identification into grey ultrasound (US) images, helping to differentiate fine details.

Developed by University of Rochester (NY, USA) researcher Professor Kevin Parker, PhD, the mathematical model is used to characterize US scattering behavior and visualize the results as color-coding of the B-scan image. The methodology, which uses a set of mathematical functions devised in 1890 by the great mathematician Charles Hermite of France, approximates the pulse-echo formation in typical situations. Professor Parker recognized that the Gaussian weighted Hermite functions closely approximated ultrasound pulses.

Currently, medical US imaging scanners typically display the envelope of the reflected signal on a log scale in shades of grey. But the properties of this image and speckle patterns result in an inability to differentiate between different scattering sources that may have fundamentally different frequency-dependent scattering cross sections. The new class of images, termed H-scan, can reveal information otherwise hidden in the conventional envelope display. The study was published in the June 2016 issue of Physics in Medicine & Biology.

“If you look at an ultrasound image of the liver, there are so many things in there – veins, arteries, biliary ducts, liver cells, perhaps some scar tissue – and they’re all just displayed as black and white blobs,” said Professor Parker, of the department of electrical and computer engineering. “If there’s a large artery, it’s easy to see the wall and the blood inside. But at the finer levels of detail, it is often impossible to tell if you’re looking at a smaller artery or 10 little cells.”

“By letting us see things we can’t see now, it could be very important to individual patients. I realized if we used these, it would make our analyses of ultrasound scattering easier,” concluded Professor Parker. “So now, instead of ultrasound images showing all of these tissue structures as black and white objects, we can now classify them mathematically (by their size) and assign unique colors to unique types of scatterers.”

Ultrasound uses pulses of high-frequency sound waves that bounce back echoes when they strike cells or arteries; these echoes are also known as scattered waves. With few exceptionssuch as Doppler-enhanced ultrasound imaging of blood flow – those features consist of varying shades of black, white, and gray reflecting different densities.

Related Links:
University of Rochester

Print article


Industry News

view channel
Image: A demonstration featuring ACR AI-LAB will allow Summit attendees to gain a better understanding of how radiologists can use ACR AI-LAB tools to learn the basics of AI and participate in the creation, evaluation and use of health care AI (Photo courtesy of ACR).

Imaging Informatics Summit Highlights Impact of AI Technologies on Patient Care

The 2019 Imaging Informatics Summit organized by the American College of Radiology {(ACR) Reston, VA, USA} will be held in Washington, D.C., USA, on October 5–6, 2019, and will focus on the role that artificial... Read more
Copyright © 2000-2019 Globetech Media. All rights reserved.