KEYWORDS: Tomography, Image segmentation, Monte Carlo methods, Performance modeling, Bone, Process modeling, Data acquisition, Analytical research, Web services, Synchrotron radiation
The Helmholtz-Zentrum Hereon is operating several tomography end stations at the beamlines P05 and P07 of the synchrotron radiation facility PETRA III at DESY in Hamburg, Germany. Attenuation and phase contrast imaging techniques are provided as well as sample environments for in situ/operando/vivo experiments for applications in biology, medicine, materials science, etc. Very large and diverse data sets with varying spatiotemporal resolution, noise levels and artifacts are acquired which are challenging to process and analyze. Here we report on an active learning approach for the semantic segmentation of tomography data using a guided and interactive framework, and evaluate different acquisition functions for the selection of images to be annotated in the iterative process.
A load frame for in situ mechanical testing is developed for the microtomography end stations at the imaging beamline P05 and the high-energy material science beamline P07 of PETRA III at DESY, both operated by the Helmholtz- Zentrum Geesthacht. The load frame is fully integrated into the beamline control system and can be controlled via a feedback loop. All relevant parameters (load, displacement, temperature, etc.) are continuously logged. It can be operated in compression or tensile mode applying forces of up to 1 kN and is compatible with all contrast modalities available at IBL and HEMS i.e. conventional attenuation contrast, propagation based phase contrast and differential phase contrast using a grating interferometer. The modularity and flexibility of the load frame allows conducting a wide range of experiments. E.g. compression tests to understand the failure mechanisms in biodegradable implants in rat bone or to investigate the mechanics and kinematics of the tessellated cartilage skeleton of sharks and rays, or tensile tests to illuminate the structure-property relationship in poplar tension wood or to visualize the 3D deformation of the tendonbone insertion. We present recent results from the experiments described including machine-learning driven volume segmentation and digital volume correlation of load tomography sequences.
Permanent implants made of titanium or its alloys are the gold standard in many orthopedic and traumatological
applications due to their good biocompatibility and mechanical properties. However, a second surgical intervention is
required for this kind of implants as they have to be removed in the case of children that are still growing or on patient’s
demand. Therefore, magnesium-based implants are considered for medical applications as they are degraded under
physiological conditions. The major challenge is tailoring the degradation in a manner that is suitable for a biological
environment and such that stabilization of the bone is provided for a controlled period. In order to understand failure
mechanisms of magnesium-based implants in orthopedic applications and, further, to better understand the
osseointegration, screw implants in bone are studied under mechanical load by means of a push-out device installed at
the imaging beamline P05 of PETRA III at DESY. Conventional absorption contrast microtomography and phasecontrast
techniques are applied in order to monitor the bone-to-implant interface under increasing load conditions. In this
proof-of-concept study, first results from an in situ push-out experiment are presented.
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