Investigation of Physical Phenomena Underlying Temporal-Enhanced Ultrasound as a New Diagnostic Imaging Technique: Theory and Simulations
| Autor: | Guy Nir, Mohammad I. Daoud, Kenneth A. Iczkowski, Shekoofeh Azizi, Septimiu E. Salcudean, Sharareh Bayat, Farhad Imani, Larry Goldenberg, Amir M. Tahmasebi, Francois Guy Gerard Marie Vignon, Pingkun Yan, Parvin Mousavi, Carlos D. Gerardo, Purang Abolmaesumi, Storey Wilson, Samira Sojoudi, M. Scott Lucia |
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| Rok vydání: | 2018 |
| Předmět: |
Male
Acoustics and Ultrasonics Backscatter Databases Factual Computer science 0206 medical engineering Finite Element Analysis 02 engineering and technology 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Sparse array Image Interpretation Computer-Assisted Humans Computer Simulation Electrical and Electronic Engineering Instrumentation Ultrasonography business.industry Phantoms Imaging Ultrasound Prostate Digital pathology Prostatic Neoplasms 020601 biomedical engineering Finite element method Data set Vibration Radio frequency Biological system business |
| Zdroj: | IEEE transactions on ultrasonics, ferroelectrics, and frequency control. 65(3) |
| ISSN: | 1525-8955 |
| Popis: | Temporal-enhanced ultrasound (TeUS) is a novel noninvasive imaging paradigm that captures information from a temporal sequence of backscattered US radio frequency data obtained from a fixed tissue location. This technology has been shown to be effective for classification of various in vivo and ex vivo tissue types including prostate cancer from benign tissue. Our previous studies have indicated two primary phenomena that influence TeUS: 1) changes in tissue temperature due to acoustic absorption and 2) micro vibrations of tissue due to physiological vibration. In this paper, first, a theoretical formulation for TeUS is presented. Next, a series of simulations are carried out to investigate micro vibration as a source of tissue characterizing information in TeUS. The simulations include finite element modeling of micro vibration in synthetic phantoms, followed by US image generation during TeUS imaging. The simulations are performed on two media, a sparse array of scatterers and a medium with pathology mimicking scatterers that match nuclei distribution extracted from a prostate digital pathology data set. Statistical analysis of the simulated TeUS data shows its ability to accurately classify tissue types. Our experiments suggest that TeUS can capture the microstructural differences, including scatterer density, in tissues as they react to micro vibrations. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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