THE CHANCES OF PRECISION ENHANCE FOR ULTRASONIC IMAGING


Abstract

The results of ultrasonic imaging with the aid of an algorithm with the virtual rays is presented in this paper. The signal associated with the virtual rays is calculated as an arithmetical mean value of the signals of the rays surrounding the virtual one. Developed algorithm was tested on synthetic free noise data then polluted synthetic data in order to move for the real measurements. Conclusions about the imaging with new algorithm are not obvious. In same cases the significant improvement was achieved but in some not.


Keywords

ultrasound tomography; inverse problems; singular value decomposition

Bartušek K., Fiala P., Mikulka J.: Numerical Modeling of Magnetic Field Deformation as Related to Susceptibility Measured with an MR System. Radioengineering 17(2)/2008, 113–118.

Bartušek K., Drexler P., Fiala P. et al.: Magnetoinductive Lens for Experimental Mid-field MR Tomograph. Progress in Electromagnetics Research Symposium Location: Cambridge 2010, 1047–1050.

Dušek J., Hladký D., Mikulka J.: Electrical Impedance Tomography Methods and Algorithms Processed with a GPU. PIERS Proceedings (Spring) 2017, 1710–1714.

Gorodinitsky I.F., George J.S., Rao B.D.: Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm. Clinical Neurophysiology 95/1995, 231–251.

Göcke L: PiCUS Sonic Tomograph Software Manual, Argus Electronic Gmbh, Erich-Schlesinger-Straße 49d, 18059 Rostock, Germany, 2017, www.argus-electronic.de.

Kak A.C., Slaney M.: Principles of Computerized Tomographic Imaging. IEEE Press, New York 1999.

Kłosowski G., Rymarczyk T.: Using Neural Networks and Deep Learning Algorithms in Elecrical Impedance Tomography. Informatyka, Automatyka Pomiary w Gospodarce i Ochronie Środowiska (IAPGOŚ) 3/2017, 99–102.

Koulountzios P., Rymarczyk T., Soleimani M.: Ultrasonic Tomography for automated material inspection in liquid masses. 9th World Congress on Industrial Process Tomography, Bath, Great Britain, 2–6 September 2018.

Lawson Ch.L., Hanson R.J.: Solving Least Squares Problems. Classics in Applied Mathematics 15/1998.

Łopato P.: Detekcja i identyfikacja defektów struktur dielektrycznych i kompozytowych z wykorzystaniem fal elektromagnetycznych w zakresie terahercowym. Wydawnictwo Uczelniane Zachodniopomorskiego Uniwersytetu Technologicznego w Szczecinie, Szczecin 2018.

Marcon P. et al.: Magnetic susceptibility measurement using 2D magnetic resonance imaging. Measurement Science and Technology, 2011, 22.10: 105702.

Mikulka J.: GPU–Accelerated Reconstruction of T2 Maps in Magnetic Resonance Imaging. Measurement Science Review 4/2015, 210–218.

Yang M., Schlaberg H.I., Hoyle B.S., Beck M.S., Lenn C.: Real-Time Ultrasound Process Tomography for Two-Phase Flow Imaging Using a Reduced Number of Transducers. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 46(3)/1999.

Polakowski K., Filipowicz S.F., Sikora J., Rymarczyk T.: Quality of imaging in multipath tomography. Przeglad Elektrotechniczny 85(12)/2009, 134–136.

Rymarczyk T., Sikora J., Waleska B.: Coupled Boundary Element Method and Level Set Function for Solving Inverse Problem in EIT. 7th World Congress on Industrial Process Tomography WCIPT7 2013, 312–319.

Rymarczyk T., Sikora J., Polakowski K., Adamkiewicz P.: Efektywny algorytm obrazowania w tomografii ultradźwiękowej i radiowej dla zagadnień dwuwymiarowych. Przegląd Elektrotechniczny 94(6)/2018.

Rymarczyk T. et al.: Sposób i układ do prowadzenia pomiarów w elektrycznej tomografii pojemnościowej. Zgłoszenie patentowe P.418304 z dnia 12.08.2016.

Smolik W.: Forward Problem Solver for Image Reconstruction by Nonlinear Optimization in Electrical Capacitance Tomography. Flow Measurement and Instrumentation 21/2010, 70–77.

Soleimani M., Mitchell C.N., Banasiak R., Wajman R., Adler A.: Four-dimensional electrical capacitance tomography imaging using experimental data. Progress in Electromagnetics Research 90/2009, 171–186.

http://www.mathworks.com/products/matlab/ (June 2018).

Download

Published : 2018-09-25


Rymarczyk, T., Sikora, J., Adamkiewicz, P., Bożek, P., & Gołąbek, M. (2018). THE CHANCES OF PRECISION ENHANCE FOR ULTRASONIC IMAGING. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 8(3), 19-24. https://doi.org/10.5604/01.3001.0012.5277

Tomasz Rymarczyk  tomasz@rymarczyk.com
1Research and Development Center, Netrix S.A., Lublin, 2University of Economics and Innovation in Lublin  Poland
Jan Sikora 
Research and Development Center, Netrix S.A., Lublin  Poland
Przemysław Adamkiewicz 
Research and Development Center, Netrix S.A., Lublin  Poland
Piotr Bożek 
Research and Development Center, Netrix S.A., Lublin  Poland
Michał Gołąbek 
Research and Development Center, Netrix S.A., Lublin  Poland