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Qua ntitative s onographic i maging of human hard tissue by m athematical modelling of scanning acoustic microscopy d

QUASIM. Qua ntitative s onographic i maging of human hard tissue by m athematical modelling of scanning acoustic microscopy data . Prof. Dr. R.Sader Prof.Dr.M.Grote Ph.Dr. L.Beilina. Main objectives. Development of quantitative sonographic imaging by mathematical modelling Testing

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Qua ntitative s onographic i maging of human hard tissue by m athematical modelling of scanning acoustic microscopy d

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  1. QUASIM Quantitative sonographic imaging of human hard tissue by mathematical modelling of scanning acoustic microscopy data Prof. Dr. R.Sader Prof.Dr.M.Grote Ph.Dr. L.Beilina

  2. Main objectives • Development of quantitative sonographic imaging by mathematical modelling • Testing • Clinical application of ultrasound diagnostics

  3. KSI – Krämer Scientific Instruments GmbH • Is a private company located in Herborn, Germany • Established in 1990 • Provide support and development for the high technology Scanning Acoustic Microscopy (SAM) • Main directions are research, nondestructive testing and the process control industry ___________________________________ www.ksi-germany.com

  4. KSI WINSAM 2000Scanning Acoustic Microscope transmitter receiver acoustic lens transducer Coupling fluid (water) sample

  5. KSI WINSAM 2000 Scan field 300 X 300 mm Scanning Acoustic Microscope Production and failure analysis Repeated information Detailed information Shows processing and in-service defects

  6. Mathematical Model ofScanning Acoustic Microscope G 1 transmitter receiver acoustic lens transducer C 0 Coupling fluid (water) G 2 G 2 C(x) sample G 2

  7. Computational mesh

  8. Computational Algorithm Solve forward problem Initial guess c=c0 Solve adjoint problem Compute gradient and new ch no If gradient > eps yes stop

  9. Adaptive Algorithm Initial guess c=c0 Solve forward problem on Kh, Tk Initial mesh K0 Construct new time partition Tk Solve adjoint problem on Kh, Tk Initial time partition T0 Construct new mesh Kh Compute gradient and new ch no If gradient decreases yes Residuals > tol refine elements no yes stop

  10. Solution of the forward problem c=0.5 inside a spherical inclusion and c=1.0 everywhere else in the domain. Isosurfaces of the computed solution are shown at different times.

  11. Solution of the forward problem Solution of the forward problem with exact value of the parameter c=0.5 inside a spherical inclusion and c=1.0 everywhere else in the computational domain. We show isosurfaces of the computed solution at different times.

  12. Adaptively refined meshes

  13. Reconstructed parameter 26133 nodes, c = 0.531 33138 nodes, c=0.51 22528 nodes, c =0.66 Reconstructed parameter c(x) on different adaptively refined meshes. Isosurfaces of the parameter field c(x) indicating domains with a given parameter value are shown.

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