Preprocessing for improved computer aided detection in medical ultrasound

Richard Mammone, Susan Love, Lev Barinov, William Hulbert, Ajit Jairaj, Christine Podilchuk

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

1 Citation (Scopus)

Abstract

Recently, a new speckle noise reduction and contrast enhancement technique has been introduced that is motivated by the research in compressive sampling or sensing. Compressive sampling is based on the principle that a sparse signal such as ultrasound can be fully recovered when sampled below the Nyquist rate. This allows for a new noise reduction technique that preserves the high frequency and fine details while reducing the effects of speckle noise. This method improves the overall perceptual quality of the image for visualization and diagnosis by the radiologist. This paper examines how the improvement in SNR makes the method suitable as a preprocessor to improve a computer aided detection (CAD) system for breast cancer detection. Classical performance metrics such as false positive rates, false negative rates and receiver operator curves will be used to show the benefits of this approach. Initial experiments look promising for microcalcification detection, where the new method yields a false negative rate of 20 percent at a false positive rate of 0.5 percent while the traditional speckle reduction techniques yield a false negative rate of 60 percent at a false positive rate of 0.5 percent.

Original languageEnglish (US)
Title of host publication2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013
PublisherIEEE Computer Society
ISBN (Print)9781479930074
DOIs
StatePublished - Jan 1 2013
Event2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013 - Brooklyn, NY, United States
Duration: Dec 7 2013Dec 7 2013

Publication series

Name2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013

Other

Other2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013
CountryUnited States
CityBrooklyn, NY
Period12/7/1312/7/13

Fingerprint

Speckle
Ultrasonics
Noise abatement
Sampling
Visualization
Experiments

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

Cite this

Mammone, R., Love, S., Barinov, L., Hulbert, W., Jairaj, A., & Podilchuk, C. (2013). Preprocessing for improved computer aided detection in medical ultrasound. In 2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013 [6736776] (2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013). IEEE Computer Society. https://doi.org/10.1109/SPMB.2013.6736776
Mammone, Richard ; Love, Susan ; Barinov, Lev ; Hulbert, William ; Jairaj, Ajit ; Podilchuk, Christine. / Preprocessing for improved computer aided detection in medical ultrasound. 2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013. IEEE Computer Society, 2013. (2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013).
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Mammone, R, Love, S, Barinov, L, Hulbert, W, Jairaj, A & Podilchuk, C 2013, Preprocessing for improved computer aided detection in medical ultrasound. in 2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013., 6736776, 2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013, IEEE Computer Society, 2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013, Brooklyn, NY, United States, 12/7/13. https://doi.org/10.1109/SPMB.2013.6736776

Preprocessing for improved computer aided detection in medical ultrasound. / Mammone, Richard; Love, Susan; Barinov, Lev; Hulbert, William; Jairaj, Ajit; Podilchuk, Christine.

2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013. IEEE Computer Society, 2013. 6736776 (2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013).

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

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Mammone R, Love S, Barinov L, Hulbert W, Jairaj A, Podilchuk C. Preprocessing for improved computer aided detection in medical ultrasound. In 2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013. IEEE Computer Society. 2013. 6736776. (2013 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2013). https://doi.org/10.1109/SPMB.2013.6736776