Advanced Reconstruction Toolbox
State-of-the-Art Reconstruction Technologies for Your ZEISS X-ray Microscope or microCT
Enrich your research and increase the ROI of your ZEISS Xradia X-ray platform
Unique Advanced Reconstruction Toolbox (ART) offerings leverage AI and a deep understanding of both X-ray physics and customer applications to solve some of the hardest imaging challenges in new and innovative ways. These optional modules are workstation-based solutions that provide easy access and usability.
Built by ZEISS with continuously developed algorithms and unique workflows. Platform for continuously launching ground-breaking innovations from ZEISS X-ray Microscopy.
Image reconstruction technologies enhance X-ray system performance:
An A12 smartphone package acquired using DeepScout
For a large field of view scan, a high res scan to train the model, and high resolution reconstruction to LFOV.
Resolution at field of view, throughput at field of view
ZEISS DeepScout uses high-resolution 3D microscopy datasets as training data for lower resolution, larger field of view datasets and upscales the larger volume data using a neural network model. ZEISS DeepScout, developed through continued algorithmic innovation enabled by the AI infrastructure from ZEISS, employs the unique Scout-and-Zoom capability to acquire richer information at higher resolution, including interior tomographies for large samples.
- Take your large overview scan
- Feed it through the ZEISS DeepScout reconstruction algorithm
- Get resolution that approaches the resolution of a Zoom scan, but over a much larger field of view.
At its core, ZEISS DeepScout relies on the ability to generate multiscale, spatially registered datasets and uses that ability to train neural networks to improve the reconstruction. New capabilities, fueled by deep learning, mitigate the traditional trade-off between field of view and resolution.
DeepScout, on the left, shows significantly more cellular information than standard reconstruction, on the right.
Sample courtesy of Keith Duncan, Donal Danforth Plant Science Center.
How it works
Polymer electrolyte fuel cell (PEFC) Now, your volume scout includes the full field of view for your sample. A selected high-resolution scan trains the whole model to provide you with high resolution at FOV! This is game-changing AI, uniquely enabling visualization of fine structure across large fields of view at unprecedented speeds.
ZEISS DeepRecon Pro
Harvest the hidden opportunities in big data generated by your XRM
The first commercially available deep learning reconstruction technology enables you to increase throughput by up to 10× without sacrificing novel resolution at a distance (RaaD). Alternatively, keep the same number of projections and enhance the image quality further. ZEISS DeepRecon provides significant AI-driven speed or image quality improvement.
ZEISS DeepRecon Pro is applicable to both unique samples as well as semi-repetitive and repetitive workflows. Self-train new machine learning network models on-site with an extremely easy-to-use interface. The one-click workflow of ZEISS DeepRecon Pro eliminates the need for a machine learning expert and can be seamlessly operated by even a novice user.
ZEISS DeepRecon Pro is now available on ZEISS Xradia Ultra nanoscale XRM.
Mouse lung imaged with Xradia Versa. Sample is iodine stained and captured with 3001 projections. Reconstruction done using DeepRecon (right). Compared with the equivalent image reconstructed using FDK (left)
fcBGA flip chip imaged with ZEISS Xradia UltraXRM
left: Standard reconstruction, 1000 projections, 18-hour scan
right: DeepRecon Pro Ultra reconstruction, 250 projections, 4.5 hour scan, a 4x improvement.
Materials Aware Reconstruction Solution (MARS)
Superior image quality for highly attenuating samples
MARS is a reconstruction algorithm that is aware of the constituents within a reconstruction. A challenge in X-ray reconstruction in a lab setting is that imaging with a polychromatic source creates different X-ray energies to generate a phenomenon called beam hardening. This effect is particularly challenging when your material is very dense and embedded in relatively less dense material. MARS tells the reconstruction system how to compensate for the effect of extreme beam hardening in the regions between very dense objects. This is important in applications like biomaterials, where you might be looking at implants next to bone or tissue. Or electronics where extremely dense solder balls appear next to other less dense materials on a printed circuit board, generating strong artifacts. MARS reconstructs your images to compensate for these effects.
Biomedical metal implant in bone. Without MARS, left. With MARS, right.
Enhanced image contrast and improved segmentation
ZEISS PhaseEvolve is a patent-pending postprocessing reconstruction algorithm that enhances the image contrast by revealing material contrast uniquely inherent to X-ray microscopy, which can often be obscured by phase effects in low-medium density samples or high-resolution datasets. Perform more accurate quantitative analysis with improved contrast and segmentation of your results.
Rayon fibers were imaged at 1.5 μm/voxel resolution and processed using ZEISS PhaseEvolve revealing the large distribution of radial porosity along the length of the fibers.
Sample courtesy Dr. Sherry Mayo & Dr. David Fox, CSIRO, Australia.
Fast and efficient iterative reconstruction solution
A fast and efficient algorithm-based technology that delivers iterative reconstruction from your desktop, allowing you to achieve up to 4× faster scan times or enhanced image quality with equivalent throughput. ZEISS OptiRecon is an economical solution offering superior interior tomography or throughput on a broad class of samples.
Camera module: 1200 projections in 90 minutes using standard FDK, left, vs. 300 projections in 22 minutes with OptiRecon, right. Comparable image quality in a fraction of the time.