Clutter noise reduction in B-Mode image through mapping and clustering signal energy for better cyst classification

Asraf Mohamed Moubark, Sevan Harput, David M J Cowell, Steven Freear

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Improving the ultrasound image contrast ratio (CR) and contrast to noise ratio (CNR) has many clinical advantages. Breast cancer detection is one example. Anechoic cysts which fill with clutter noise can be easily misinterpreted and classified as malignant lesions instead of benign. Beamforming techniques contribute to off-axis side lobes and clutter. These two side effects inherent in beamforming are undesirable since they will degrade the image quality by lowering the image CR and CNR. To overcome this issue a new post-processing technique known as contrast enhanced delay and sum (CEDAS) is proposed. Here the energy of every envelope signals are calculated, mapped, and clustered in order to identify the cyst and clutter location. CEDAS reduce clutter inside the cyst by attenuating it from envelope signals before the new B-Mode image is formed. With CEDAS, the image CR and CNR improved by average 12 dB and 1.1 dB respectively for cysts size 2 mm to 6 mm and imaging depth from 40 mm to 80 mm.

Original languageEnglish
Title of host publication2016 IEEE International Ultrasonics Symposium, IUS 2016
PublisherIEEE Computer Society
Volume2016-November
ISBN (Electronic)9781467398978
DOIs
Publication statusPublished - 1 Nov 2016
Externally publishedYes
Event2016 IEEE International Ultrasonics Symposium, IUS 2016 - Tours, France
Duration: 18 Sep 201621 Sep 2016

Other

Other2016 IEEE International Ultrasonics Symposium, IUS 2016
CountryFrance
CityTours
Period18/9/1621/9/16

Fingerprint

cysts
clutter
noise reduction
image contrast
beamforming
energy
envelopes
breast
lobes
lesions
cancer

ASJC Scopus subject areas

  • Acoustics and Ultrasonics

Cite this

Mohamed Moubark, A., Harput, S., Cowell, D. M. J., & Freear, S. (2016). Clutter noise reduction in B-Mode image through mapping and clustering signal energy for better cyst classification. In 2016 IEEE International Ultrasonics Symposium, IUS 2016 (Vol. 2016-November). [7728860] IEEE Computer Society. https://doi.org/10.1109/ULTSYM.2016.7728860

Clutter noise reduction in B-Mode image through mapping and clustering signal energy for better cyst classification. / Mohamed Moubark, Asraf; Harput, Sevan; Cowell, David M J; Freear, Steven.

2016 IEEE International Ultrasonics Symposium, IUS 2016. Vol. 2016-November IEEE Computer Society, 2016. 7728860.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mohamed Moubark, A, Harput, S, Cowell, DMJ & Freear, S 2016, Clutter noise reduction in B-Mode image through mapping and clustering signal energy for better cyst classification. in 2016 IEEE International Ultrasonics Symposium, IUS 2016. vol. 2016-November, 7728860, IEEE Computer Society, 2016 IEEE International Ultrasonics Symposium, IUS 2016, Tours, France, 18/9/16. https://doi.org/10.1109/ULTSYM.2016.7728860
Mohamed Moubark A, Harput S, Cowell DMJ, Freear S. Clutter noise reduction in B-Mode image through mapping and clustering signal energy for better cyst classification. In 2016 IEEE International Ultrasonics Symposium, IUS 2016. Vol. 2016-November. IEEE Computer Society. 2016. 7728860 https://doi.org/10.1109/ULTSYM.2016.7728860
Mohamed Moubark, Asraf ; Harput, Sevan ; Cowell, David M J ; Freear, Steven. / Clutter noise reduction in B-Mode image through mapping and clustering signal energy for better cyst classification. 2016 IEEE International Ultrasonics Symposium, IUS 2016. Vol. 2016-November IEEE Computer Society, 2016.
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