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Tissue typing with ultrasound RF time series: phantom studies Moradi, Mehdi; Rohling, Robert N.; Mousavi, Parvin; Abolmaesumi, Purang
Abstract
We report phantom studies on a new approach to ultrasound-based tissue typing. In the proposed approach, we continuously record RF echo signals backscattered from tissue, while the imaging probe and the tissue are fixed in position. The continuously recorded RF data generates a time series of echoes for each spatial sample of the RF signal. We use the spectral and fractal features of ultrasound RF time series averaged over a region of interest, along with support vector machine classifiers, for tissue typing. In this paper, the effects of two properties of tissue on RF time series are investigated: cell size and elasticity. We show that RF time series acquired from agar-gelatin based tissue mimicking phantoms, with difference only in the size of cell-mimicking glass beads, are distinguishable with statistically reliable accuracies up to 82.2%. Similar experiments using phantoms with different elastic properties did not result in consistently high classification accuracies. The results of this study confirm that the evident differences in microstructure of the cancerous versus normal tissue could play a role in the success of the proposed tissue typing method in detection of prostate cancer. Copyright 2009 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Item Metadata
Title |
Tissue typing with ultrasound RF time series: phantom studies
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Creator | |
Publisher |
Society of Photo-Optical Instrumentation Engineers (SPIE)
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Date Issued |
2009
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Description |
We report phantom studies on a new approach to ultrasound-based tissue typing. In the proposed approach, we continuously record RF echo signals backscattered
from tissue, while the imaging probe and the tissue are fixed in position. The continuously recorded RF data generates a time series of echoes for each spatial
sample of the RF signal. We use the spectral and fractal features of ultrasound RF time series averaged over a region of interest, along with support vector
machine classifiers, for tissue typing. In this paper, the effects of two properties of tissue on RF time series are investigated: cell size and elasticity.
We show that RF time series acquired from agar-gelatin based tissue mimicking phantoms, with difference only in the size of cell-mimicking glass beads, are
distinguishable with statistically reliable accuracies up to 82.2%. Similar experiments using phantoms with different elastic properties did not result in
consistently high classification accuracies. The results of this study confirm that the evident differences in microstructure of the cancerous versus normal
tissue could play a role in the success of the proposed tissue typing method in detection of prostate cancer.
Copyright 2009 Society of Photo-Optical Instrumentation Engineers.
One print or electronic copy may be made for personal use only. Systematic reproduction and distribution,
duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
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Genre | |
Type | |
Language |
eng
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Date Available |
2011-07-05
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0107545
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URI | |
Affiliation | |
Citation |
Moradi, Mehdi; Rohling, Robert N.; Mousavi, Parvin; Abolmaesumi, Purang. Tissue typing with ultrasound RF time series: phantom studies. Medical Imaging 2009: Ultrasonic Imaging and Signal Processing, edited by Stephen A. McAleavey, Jan D'hooge Proceedings of SPIE Volume 7265, 726516, 2009.
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Publisher DOI |
10.1117/12.811693
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Peer Review Status |
Reviewed
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Scholarly Level |
Faculty
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Copyright Holder |
Rohling, Robert N.
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International