Paper 14085-12
Optical scanning tomography elastography: experimental validation of a novel elastography method
16 April 2026 • 15:30 - 15:50 CEST | Luxembourg/Salon 2 (Niveau/Level 0)
Abstract
We present a measurement technique for resolving 4D (3D + time) displacement fields within very soft, transparent phantoms subjected to forced harmonic mechanical loading along with a complimentary Nonlinear Inversion (NLI) reconstruction method using this volumetric data. The method combines Stationary Optical Scanning Tomography (S‑OST) with Digital Volume Correlation (DVC) to obtain volumetric displacement fields in tissue‑mimicking materials commonly used in elastography. The optical acquisition scheme is adapted to steady‑state harmonic motion by synchronizing a scanning laser sheet, a high‑speed camera and the mechanical excitation. Dedicated geometric models are introduced to correct for perspective and refraction effects on both the incident laser beam and scattered light, and a grey‑level attenuation correction is applied to homogenize image contrast throughout the volume. Displacement fields are computed by DVC and post‑processed using a spatiotemporal least‑squares projection onto harmonic basis functions in order to robustly estimate complex-valued displacement and strain fields at the actuation frequency. These harmonic displacement fields are then interpreted by a subzone-based NLI reconstruction algorithm to generate full volume, 3D maps of the viscoelastic properties of the sample. The method is assessed using multiple phantom configurations: homogeneous, bi‑layer, and inclusion‑containing geometries. Results demonstrate highly resolved, repeatable displacement fields with sensitivity to heterogeneities and good agreement with theoretical wavefield predictions. This OST Elastography framework provides a practical, low‑cost experimental tool for development, calibration, and validation of elastography methods, particularly in complex viscoelastic phantoms where conventional clinical imaging approaches are difficult to interpret.
Presenter
Elijah Van Houten
ICube, CNRS (France), Univ. de Strasbourg (France)
Elijah Van Houten was born and raised in the White Mountains of northern New Hampshire, in the USA. He received his B.S. degree in Mechanical Engineering and a B.A. degree in Music from Tufts University, Boston, USA, and his Ph.D. degree in Engineering Science from the Thayer School of Engineering at Dartmouth College. After completing his Ph.D. and a postdoctoral fellowship at Dartmouth, Elijah took on a faculty position in Computational Mechanics at the University of Canterbury in Christchurch, New Zealand. From New Zealand, he moved to a professorship in Numerical Methods at the Université de Sherbrooke, in Québec, Canada. Now, Elijah has made another international move to take up a position as a CNRS Research Director in the Robotics, Data science and Healthcare technologies team at the ICube laboratory in Strasbourg.