ZEISS ZEN Intellesis for Image Segmentation in Microscopy

Use the Power of Deep Learning to Easily Segment Your Images

As enjoyable as microscopic images are - their real value is in the data they provide. Image segmentation is currently one of the biggest challenges in microscopy. Segmentation lays the foundation for all subsequent image analysis steps. ZEN Intellesis uses deep learning and Python to easily create robust and reproducible segmentation results, even for non-experts. You can now train the software once and then ZEN Intellesis can segment a batch of hundreds of images automatically. You save time and minimize user bias.

Highlights
Application Examples
How to Segment Your Images
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Highlights

Use Deep Learning to Segment Your Images

To get from nice images to reliable data, you often need to segment multiple classes of objects in multiple images. With ZEN Intellesis you can now use your expertise to train the software on a few images. All time consuming segmentation steps on the hundreds of similar images will then be done by the powerful deep learning algorithms and the Python infrastructure of the software module ZEN Intellesis. With real multichannel feature extraction, even complex multidimensional, multi-modal data can be analyzed, regardless of their origin.

Enjoy Smooth Workflow Integration

The software module ZEN Intellesis makes deep learning easy to use: You simply load your image, define your classes, label objects, train your model and perform the image segmentation. When you’re satisfied with the results, you apply the trained model to segment and analyze full datasets. ZEN Intellesis is fully integrated into the Image Analysis Wizard in ZEN Imaging Software. The integration into the ZEN measurement framework makes sure that all valuable Metadata stay connected and are available for further processing steps.

Analyze Multi-Modal Images from Many Sources, in Many Formats

With the software module ZEN Intellesis you can easily segment multidimensional images from a wealth of different sources, as diverse as

  • Widefield Microscopy
  • Superresolution Microscopy
  • Fluorescence Microscopy
  • Label Free Microscopy
  • Confocal Microscopy
  • Light Sheet Microscopy
  • Electron Microscopy
  • X-ray Microscopy

And you can analyze all image formats which ZEN imaging software can read: CZI, TIFF, JPG, PNG, TXM and all Bio-Formats compatible images.

Application Example Life Sciences

1. Scratch Assay

Single frame of recorded time-lapse movie. Segmentation result of ZEN Intellesis
Single frame of recorded time-lapse movie.
Segmentation result of ZEN Intellesis - scratch area (turquoise), cell layer (orange) and mitotic cells (red).
scratch area measured over time
Based on ZEN Intellesis segmentation results, the size of the scratch area was measured over time using the ZEN Image Analysis module.

2. Spines and Dendrites

spines on a dendrite
Dendrite of a neuron expressing Green Fluorescent Protein. Image acquired with structured illumination on an Elyra PS.1 showing spines on a dendrite.
Segmentation with ZEN Intellesis results in a clear separation
Segmentation with ZEN Intellesis results in a clear separation of spines (green) from dendrite (red) and background (blue)

3. Drosophila

X-Ray micrograph of a Drosophila melanogaster.
X-Ray micrograph of a Drosophila melanogaster. 1400 slide z-stack of the whole fruit fly acquired with ZEISS 520 Versa.
X-Ray micrograph of a Drosophila melanogaster.
Segmentation result obtained with ZEN Intellesis – exoskeleton (red), inner structures (blue and yellow), background (green)
X-Ray micrograph of a Drosophila melanogaster.
Rendered 3D model based on exoskeleton class.

Application Example Materials Analysis

XRM Sandstone – Original
XRM Sandstone – Original
XRM Sandstone – Labeled
XRM Sandstone – Labeled
XRM Sandstone – Trained & Segmented
XRM Sandstone – Trained & Segmented
XRM Sandstone – IP Function Output
XRM Sandstone – IP Function Output

How to Segment Your Images

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ZEISS ZEN Intellesis Machine Learning Software

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