New denoising technique for ultrasound images using morphological properties of speckle combined with tissue classifying parameters

Gjenna Stippel; Wilfried R. Philips; Ignace L. Lemahieu

doi:10.1117/12.462169

11 April 2002 New denoising technique for ultrasound images using morphological properties of speckle combined with tissue classifying parameters

Gjenna Stippel, Wilfried R. Philips, Ignace L. Lemahieu

Author Affiliations +

Proceedings Volume 4687, Medical Imaging 2002: Ultrasonic Imaging and Signal Processing; (2002) https://doi.org/10.1117/12.462169
Event: Medical Imaging 2002, 2002, San Diego, California, United States

Abstract

In this paper we introduce a new speckle suppression technique for medical ultrasound images that incorporates morphological properties of speckle as well as tissue classifying parameters. Each individual speckles is located, and, exploiting our prior knowledge on the tissue classification, it is determined whether this speckle is noise or a medically relevant detail. We apply the technique on images of neonatal brains affected by White Matter Damage (leukomalacia). The results show that applying an active contour on a processed image, in order to segment the affected areas, yields a segmentation much closer to that of an expert.

Citation Download Citation

Gjenna Stippel, Wilfried R. Philips, and Ignace L. Lemahieu "New denoising technique for ultrasound images using morphological properties of speckle combined with tissue classifying parameters", Proc. SPIE 4687, Medical Imaging 2002: Ultrasonic Imaging and Signal Processing, (11 April 2002); https://doi.org/10.1117/12.462169

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available