Transcranial enhanced Ultrasound Imaging of induced substantia nigra in brain using adaptive Third Order Volterra Filter: In-vivo results

James Cunningham, Justice Lee, Thyagarajan Subramanian, Mohamed Khaled Almekkawy

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

4 Scopus citations

Abstract

Hyperechogenicity of the substantia nigra (SN) in the 'butterfly shaped' midbrain is a widely recognized diagnostic marker to differentiate between the early stages of Parkinsons Disease (PD) and other diseases which cause parkinsonian symptoms. While clinical differentiation of these diseases can be difficult, hyperechogenicity of the SN is only common in PD patients. Transcranial B-mode Ultrasound Imaging (TCUI) has become a heavily relied upon method to detect echogenicity in the brain. While standard B-mode imaging can show the presence of SN hyperechogenicity, it may not be able to do so with high enough specificity for reliably accurate diagnoses. The cutoff of what is considered a normal echogenic size is 0.2cm2. Clearly, boundary definition is of the utmost importance to avoid overestimating the size of the echogenic area. Many studies have shown that the harmonic component of ultrasound images have better dynamic range than standard B-mode images. That is, the images show greater contrast between light and dark regions, so low energy noise signals are less likely to show up in the image. Whereas a simple bandpass filter across the harmonic frequency would contain interference from the noisy fundamental component due to overlap of the frequency bands. We propose the use of an adaptive Third Order Volterra Filter (TOVF), which is a nonlinear filter that separates a B-mode image into its linear, quadratic, and cubic components regardless of spectral overlap. This paper investigates several variants of the commonly used adaptive Least Mean Squared (LMS) algorithm for determining filter coefficients, and their potential to improve dynamic range and resolution in B-mode images compared to a standard LMS algorithm. We found that several variant algorithms indeed show improvement in terms of Power Spectral Density (PSD) at the harmonics.

Original languageEnglish (US)
Title of host publication2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017
PublisherIEEE Computer Society
Pages684-687
Number of pages4
ISBN (Electronic)9781509011711
DOIs
StatePublished - Jun 15 2017
Event14th IEEE International Symposium on Biomedical Imaging, ISBI 2017 - Melbourne, Australia
Duration: Apr 18 2017Apr 21 2017

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other14th IEEE International Symposium on Biomedical Imaging, ISBI 2017
CountryAustralia
CityMelbourne
Period4/18/174/21/17

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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