Quantitative parametric imaging by ultrasound computed tomography of trees under anisotropic conditions: Numerical case study.

A method for the reconstruction of 2D tomographic images adapted to wood was presented, aiming to perform a nondestructive evaluation of standing trees. The proposed method takes into account the orthotropy property of wood material, performing an iterative process that approximated the curved rays. A slowness function was defined for every cell and a nonlinear regression allowed the mapping of the inner elastic constants. Four numerical configurations were tested representing real cases usually found in standing tree monitoring. These specific configurations allowed this work to focus on the analysis of the effect of anisotropy on image reconstruction. The reconstructed images using the proposed method were compared with a straight-ray reconstruction method (filtered back projection algorithm), highlighting a more detailed identification and quantification of the inner state of the anisotropic structure of the trunk.

[1]  Avinash C. Kak,et al.  Principles of computerized tomographic imaging , 2001, Classics in applied mathematics.

[2]  Roberto Martinis,et al.  Tomographie ultrasonore pour les arbres sur pied , 2004 .

[3]  Robert J. Ross,et al.  Acoustic tomography for decay detection in red oak trees , 2007 .

[4]  Flavio Prieto,et al.  Automatic segmentation of acoustic tomography images for the measurement of wood decay , 2016, Wood Science and Technology.

[5]  Hansruedi Maurer,et al.  A simple anisotropy correction procedure for acoustic wood tomography , 2006 .

[6]  F. Prieto,et al.  Effect of wood anisotropy in ultrasonic wave propagation: A ray‐tracing approach , 2019, Ultrasonics.

[7]  F. Prieto,et al.  Sensitivity of Ultrasonic Wave Velocity Estimation Using the Christoffel Equation for Wood Non-Destructive Characterization , 2017 .

[8]  Elena Comino,et al.  FEASIBILITY OF ULTRASONIC TOMOGRAPHY FOR NONDESTRUCTIVE TESTING OF DECAY ON LIVING TREES , 2004 .

[9]  V. Vinje,et al.  3-D ray modeling by wavefront construction in open models , 1999 .

[10]  Travel-time ultrasonic computed tomography applied to quantitative 2-D imaging of standing trees: a comparative numerical modeling study , 2014 .

[11]  Lei Liu,et al.  Acoustic tomography based on hybrid wave propagation model for tree decay detection , 2018, Comput. Electron. Agric..

[12]  Prof. Voichita Bucur Nondestructive Characterization and Imaging of Wood , 2003, Springer Series in Wood Science.

[13]  Giovanni Nicolotti,et al.  Application and comparison of three tomographic techniques for detection of decay in trees , 2003 .

[14]  Martin Vetterli,et al.  Robust ultrasound travel-time tomography using the bent ray model , 2010, Medical Imaging.

[15]  Traveltime computation by wavefront‐orientated ray tracing , 2005 .

[16]  Flavio Prieto,et al.  Literature review of acoustic and ultrasonic tomography in standing trees , 2014, Trees.

[17]  Cuiping Li,et al.  Travel time denoising in ultrasound tomography , 2012, Medical Imaging.

[18]  Pier Paolo Delsanto,et al.  Ultrasonic tomography using curved ray paths obtained by wave propagation simulations on a massively parallel computer , 1996 .

[19]  Håvar Gjøystdal,et al.  Traveltime and amplitude estimation using wavefront construction , 1993 .

[20]  Y. Tomikawa,et al.  Nondestructive Inspection of a Wooden Pole Using Ultrasonic Computed Tomography , 1986, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[21]  A practical implementation of wave front construction for 3-D isotropic media , 2008 .