Ultrasound contrast agents modeling using an extended Volterra model
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1 Ultrasound contrast agents modeling using an extended Volterra model FSbeity 1 J-MGirault 1 S Ménigot 1 JCharara 2 1 Université François Rabelais, Tours INSERM U930: Imagerie et cerveau 2 Lebanese University 26 April 2012 Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
2 Introduction Summary Introduction Ultrasound imaging Limitations and solutions Sub and ultra harmonic imaging Volterra model Extended Volterra model Simulation results Conclusion and perspectives Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
3 Introduction Ultrasound imaging Ultrasound imaging Emission and reception at the same frequency Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
4 Introduction Ultrasound Conrast Agents (UCA) Gaz microbubbles: mean diameter 1 to 10µm Injection in the venous circualtion Nonlinear behavior: generation of harmonics Harmonic imaging Harmonic imaging: emission at the frequency f and reception at the first harmonic 2f Contrast enhancement Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
5 Introduction Ultrasound Conrast Agents (UCA) Gaz microbubbles: mean diameter 1 to 10µm Injection in the venous circualtion Nonlinear behavior: generation of harmonics Harmonic imaging Harmonic imaging: emission at the frequency f and reception at the first harmonic 2f Contrast enhancement Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
6 Introduction Ultrasound Conrast Agents (UCA) Gaz microbubbles: mean diameter 1 to 10µm Injection in the venous circualtion Nonlinear behavior: generation of harmonics Harmonic imaging Harmonic imaging: emission at the frequency f and reception at the first harmonic 2f Contrast enhancement Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
7 Introduction Ultrasound Conrast Agents (UCA) Gaz microbubbles: mean diameter 1 to 10µm Injection in the venous circualtion Nonlinear behavior: generation of harmonics Harmonic imaging Harmonic imaging: emission at the frequency f and reception at the first harmonic 2f Contrast enhancement Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
8 Introduction Ultrasound Conrast Agents (UCA) Gaz microbubbles: mean diameter 1 to 10µm Injection in the venous circualtion Nonlinear behavior: generation of harmonics Harmonic imaging Harmonic imaging: emission at the frequency f and reception at the first harmonic 2f Contrast enhancement Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
9 Introduction 20 Amplitude (db) Frequency(MHz) Amplitude (db) Frequency (MHz) Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
10 Introduction 20 Amplitude (db) Frequency(MHz) Amplitude (db) Frequency (MHz) The optimal postprocessing is the Volterra/NARMA filtering include just after slide 9 and 10 Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
11 Introduction Limitations and solutions Limitations and solutions However, whatever the used postprocessing technique, there are some limitations: Limitations Non linearity of tissue Contrast reduction Solutions in postprocessing point of view Super harmonic imaging Sub and ultra harmonic imaging Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
12 Introduction Limitations and solutions Limitations and solutions However, whatever the used postprocessing technique, there are some limitations: Limitations Non linearity of tissue Contrast reduction Solutions in postprocessing point of view Super harmonic imaging Sub and ultra harmonic imaging Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
13 Introduction Limitations and solutions Limitations and solutions However, whatever the used postprocessing technique, there are some limitations: Limitations Non linearity of tissue Contrast reduction Solutions in postprocessing point of view Super harmonic imaging Sub and ultra harmonic imaging Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
14 Introduction Sub and ultra harmonic imaging Sub and ultra harmonic imaging Sub harmonic imaging post processing (Volterra/NARMA) f/2 Image f f/2 f 3f/2 2f Emission Medium (UCA) Reception Harmonic imaging post processing (Volterra/NARMA) 2f Image f 2f Ultra harmonic imaging post processing (Volterra/NARMA) 3f/2 Image Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
15 Volterra model Summary Introduction Ultrasound imaging Limitations and solutions Sub and ultra harmonic imaging Volterra model Extended Volterra model Simulation results Conclusion and perspectives Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
16 Volterra model Volterra model Nonlinear polynomial filter Efficient to model nonlinear systems m ŷ(n) = h 0 + h 1 (i 1 )x(n i 1 ) i 1=1 Microbubble y(n) x(n) - Volterra model V H m 0 ^ y (n) H e(n) m: memory of the model Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
17 Volterra model Volterra model Nonlinear polynomial filter Efficient to model nonlinear systems ŷ(n) = h m i 1=1 i 2=1 m m h 1 (i 1 )x(n i 1 ) i 1=1 m h 2 (i 1, i 2 )x(n i 1 )x(n i 2 ) m i 1=1 i 2=1 i 3=1 m h 3 (i 1, i 2, i 3 )x(n i 1 )x(n i 2 )x(n i 3 ) Microbubble x(n) - Volterra model V H m 0 y(n) ^ y (n) H e(n) m: memory of the model Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
18 Volterra model Volterra model Emission frequency: 4 MHz Microbubble Volterra model Efficient to extract harmonics Problematic: Unable to extract sub and ultra harmonics Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
19 Extended Volterra model Summary Introduction Ultrasound imaging Limitations and solutions Sub and ultra harmonic imaging Volterra model Extended Volterra model Simulation results Conclusion and perspectives Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
20 Extended Volterra model Extended Volterra model As Volterra model does not work, we propose to extend its formulation to sub and ultra harmonics step 1) Volterra model Harmonic signal step 2) Modulation Volterra model Demodulation Sub and ultra harmonic signal Sub and ultraharmonic modeling and extraction Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
21 Simulation results Summary Introduction Ultrasound imaging Limitations and solutions Sub and ultra harmonic imaging Volterra model Extended Volterra model Simulation results Conclusion and perspectives Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
22 Simulation results Simulation results Emmision frequency: f = 4MHz Pressure (Pa) Pressure (Pa) Time (µs) Time (µs) Pressure (Pa) Time (µs) (a) (b) (c) Microbubble Extended Volterra Amplitude (db) Amplitude (db) Amplitude (db) (a) 50 Microbubble Extended Volterra Frequency (MHz) (c) 50 Microbubble Volterra Frequency (MHz) (d) Microbubble Second part of extended Volterra Frequency (MHz) Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
23 Simulation results Simulation results Relative mean square error RMSE between the microbubble backscattered signal and the modeled signals Model Standard Volterra Extended Volterra RMSE (db) Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
24 Conclusion and perspectives Summary Introduction Ultrasound imaging Limitations and solutions Sub and ultra harmonic imaging Volterra model Extended Volterra model Simulation results Conclusion and perspectives Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
25 Conclusion and perspectives Conclusion and perspectives Conclusion Extended Volterra model is able to: Model microbubble signal in presence of sub and ultraharmonics Extract and separate sub and ultraharmonic signal Make possible to realize sub and ultra harmonic imaging Perspectives Separate sub harmonic components apart of ultra harmonic components Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
26 Conclusion and perspectives Conclusion and perspectives Conclusion Extended Volterra model is able to: Model microbubble signal in presence of sub and ultraharmonics Extract and separate sub and ultraharmonic signal Make possible to realize sub and ultra harmonic imaging Perspectives Separate sub harmonic components apart of ultra harmonic components Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
27 Conclusion and perspectives Conclusion and perspectives Conclusion Extended Volterra model is able to: Model microbubble signal in presence of sub and ultraharmonics Extract and separate sub and ultraharmonic signal Make possible to realize sub and ultra harmonic imaging Perspectives Separate sub harmonic components apart of ultra harmonic components Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
28 Conclusion and perspectives Conclusion and perspectives Conclusion Extended Volterra model is able to: Model microbubble signal in presence of sub and ultraharmonics Extract and separate sub and ultraharmonic signal Make possible to realize sub and ultra harmonic imaging Perspectives Separate sub harmonic components apart of ultra harmonic components Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
29 Conclusion and perspectives Thank you for your attention Any questions? Fatima Sbeity (UFR,INSERM U930) Acoustics April / 17
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