Paper
13 March 2009 Tissue typing with ultrasound RF time series: phantom studies
Author Affiliations +
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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mehdi Moradi, Parvin Mousavi, Robert Rohling, and Purang Abolmaesumi "Tissue typing with ultrasound RF time series: phantom studies", Proc. SPIE 7265, Medical Imaging 2009: Ultrasonic Imaging and Signal Processing, 726516 (13 March 2009); https://doi.org/10.1117/12.811693
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KEYWORDS
Tissues

Ultrasonography

Particles

Control systems

Feature extraction

Glasses

Prostate

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