ZEISS Advanced Reconstruction Toolbox

Better image quality, higher throughput

ZEISS Advanced Reconstruction Toolbox

Better image quality, higher throughput

For more information click to enlarge the graphic

Advanced Reconstruction Toolbox (ART) introduces Artificial Intelligence (AI)-driven reconstruction technologies on your ZEISS Xradia 3D X-ray microscope (XRM) or microCT. A deep understanding of both X-ray physics and applications enable you to solve some of the hardest imaging challenges in new and innovative ways.

Discover how speed of data acquisition and reconstruction as well as image quality are enhanced without sacrificing resolution by using OptiRecon, two variants of DeepRecon and PhaseEvolve, the unique modules of ART.

With the Advanced Reconstruction Toolbox, you are able to:

Improve data collection and analysis for accurate and faster decision-making
Greatly enhance image quality
Achieve superior interior tomography or throughput on a broad class of samples
Reveal subtle difference through improved contrast-to-noise
Increase speed at an order of magnitude for sample classes requiring repetitive workflow

3D X-ray dataset of a camera lens acquired using ZEISS Xradia 620 Versa and DeepRecon Pro.

ZEISS DeepRecon Pro provides a straightforward, uncomplicated, and powerful application of AI and deep neural network technology for enhancing X-ray tomography results without prior knowledge on deep learning technology. [...] It helps us to reduce the scan time required for in situ fluid-rock interaction experiments when we need to work with long exposure times.
Dr. Markus Ohl | X-Ray microscopy | EPOS-NL MINT | Utrecht University, NL

Watch the whole customer interview collapse

ZEISS DeepRecon Pro & Custom for Deep learning-based reconstruction

Increase the speed of your data acquisition with reconstruction technology

DeepRecon technology is offered in two forms - DeepRecon Pro and DeepRecon Custom - both leveraging AI and enhancing image quality and speed. Increase throughput without sacrificing RaaD (resolution-at-a-distance). Alternatively, keep the same number of projections and enhance the image quality further.

DeepRecon Pro used for throughput improvement for Ceramic Matrix Composite (CMC) sample, achieving 10× throughput improvement without sacrificing image quality. This would allow for much higher temporal resolution for in situ studies. Left: Standard reconstruction (FDK): Scan time 9 hrs (3001 projections). Center: Standard reconstruction (FDK): Scan time 53 mins (301 projections). Right: DeepRecon Pro: Scan time 53 mins (301 projections).

Find out the difference:

With DeepRecon Pro you benefit from superior throughput and image quality across a wide range of applications.
It enables you to reveal subtle differences in the images of your samples through improved contrast-to-noise.
Increase the speed of your data acquisition up to 10x for sample classes requiring a repetitive workflow.
Apply DeepRecon Pro to unique samples, to semi-repetitive and repetitive workflows.
Now you can self-train new machine learning network models on-site with an easy-to-use interface.
The need for a machine learning expert is thus eliminated and DeepRecon Pro can be seamlessly operated by even a novice user.

ZEISS DeepRecon Custom is targeted specifically for repetitive workflow applications to further boost XRM performance beyond DeepRecon Pro.
ZEISS collaborates closely with users to develop custom-created network models that fit their repetitive application needs precisely.

Application Examples

Ceramic Matrix Composite (CMC) - 10X Throughput Improvement

10X throughput improvement without sacrificing image quality.

Cell Phone Camera Lens - 10X Throughput Improvement

10X throughput improvement

Smartwatch Battery - 4X Throughput Improvement

4X throughput improvement while maintaining detail in cathode particles.

Smartwatch Battery - Image Quality Improvement

Enhanced image quality to see low contrast graphite particles

21700 Cylindrical Cell Battery - 8X Throughput Improvement

8X throughput improvement with comparable image quality

DRAM Semiconductor Package – 4X Throughput Improvement

4X throughput improvement

HBM-microbump Semiconductor Package – 4X Throughput Improvement

4X throughput improvement

2.5D Semiconductor Interposer Package – 4X Throughput Improvement

4X throughput improvement while retaining 1 µm crack

2.5D Semiconductor Interposer Package – Improved Image Quality

Improved image quality with same scan time.

Sandstone Core – 6X Throughput Improvement

6X throughput improvement with improved image quality and reduced imaging artefact in the imaging of sandstone rock cores enables more accurate segmentation, quantification and simulation.

Sandstone Rock (interior tomography) - Improved Segmentation and Image Quality

Plant Tissue - Improved Image Quality

Improved image quality

Application Examples collapse

ZEISS OptiRecon for iterative reconstruction

Similar results, 4x faster

ZEISS OptiRecon is an implementation of iterative reconstruction that greatly increases acquisition throughput, while optimizing image quality.

Achieve up to 4× faster scan times or enhanced image quality with equivalent throughput.
Benefit from this economical solution offering superior interior tomography or throughput on a broad class of samples.

Observe the performance of OptiRecon in a workflow performed on an electronics sample. Analyze integration issues in a smart phone camera lens, now 4× faster. Left: Standard reconstruction: Scan time 90 minutes (1200 projections). Center: Standard reconstruction: Scan time 22 minutes (300 projections). Right: OptiRecon: Scan time 22 minutes (300 projections).

Mobile phone camera module demonstrating 4X throughput improvement with comparable image quality

Slide right to left to compare:

Standard Reconstruction

OptiRecon

Application in more detail collapse

Application Examples

4X Throughput for Cell Phone Camera Lens

4X Throughput for Building Materials & Concrete

4X Throughput for Mining Powder

Flexibility for Rock Exploration
– Image Quality vs. Throughput

4X Throughput for Industrial manufacturing analysis

4X Throughput for Battery Research

Flexibility for Battery Research
– Image Quality vs. Throughput

2X Throughput for Smartwatch Battery

2X Throughput for 2.5D Semiconductor Package (50 mm x 75 mm)

Improved Image Quality for 2.5D Semiconductor Package (50 mm x 75)

2X Throughput for Semiconductor Package

Improved Image Quality for Semiconductor Package

Application in more detail collapse

ZEISS PhaseEvolve for contrast enhancement

What if your image contrast of which you know is uniquely inherent to

X-ray microscopy is overprinted by phase effects in low-medium density samples, or high resolution datasets?

Use PhaseEvolve, a post-processing reconstruction algorithm.
It enables you to enhance your image contrast.
Perform more accurate quantitative analysis with improved contrast
and segmentation of your results.

_{The image on the right shows an application of PhaseEvolve to a pharmaceutical powder sample. High resolution or low kV imaging can result in inherent material contrast being obscured by phase contrast artifacts. PhaseEvolve effectively removes phase fringes to enhance image contrast and improve segmentation results.}

Standard reconstruction

PhaseEvolve applied reconstruction

Register for the upcoming AZO webinar on 7th of September

AI-driven Reconstruction Technologies Enable Next Generation XRM Imaging:
Increase Throughput and Enhance Image Quality

In case of questions or to learn how to upgrade your
3D X-ray microscope with advanced reconstruction technologies

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ZEISS Advanced Reconstruction Toolbox

Better image quality, higher throughput

ZEISS Advanced Reconstruction Toolbox

Better image quality, higher throughput

ZEISS DeepRecon Pro & Custom for Deep learning-based reconstruction

Increase the speed of your data acquisition with reconstruction technology

Application Examples

ZEISS OptiRecon for iterative reconstruction

Similar results, 4x faster

Application Examples

ZEISS PhaseEvolve for contrast enhancement

Register for the upcoming AZO webinar on 7th of September

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