These techniques are first spatially registered before training a classifier, operating on both datasets at the same time.

In a geological example, a researcher might study sulfide mineralogical distribution using both coaxial light and backscattered electron imaging modalities. ZEISS ZEN Intellesis also works with 6D datasets, including multichannel 3D stacks or tile images. It uniquely allows for multiple spatially registered datasets, acquired using correlative microscopy and classical image analysis tools, to be used in parallel during classification. It applies that trained classifier across large, multi-dimensional datasets. ZEISS ZEN Intellesis allows users to train machine learning classifications on ZEISS image data sets as well as on any images readable by ZEISS ZEN software for any ZEISS microscopes. This enables them to easily and intelligently obtain scalable, quantitative insight. By adding robust new capabilities like machine learning to our microscopy systems, we are initiating a step-change in the way our customers in industry and academia manage and process vast amounts of imaging data generated by a range of imaging modalities. Markus Weber, Co-CEO of the ZEISS Microscopy Business Group, says, ZEISS ZEN Intellesis is an important first step in our goal to rapidly bring new solutions to our customers through digitalization.

ZEISS ZEN Intellesis software is available for the company's full range of optical, confocal, X-ray, electron and ion microscopes.ĭr. The first algorithmic solution introduced by the ZEISS ZEN Intellesis platform makes integrated, easy to use, powerful segmentation for 2D and 3D datasets available to the routine microscopy user. Today ZEISS announces ZEISS ZEN Intellesis, a new machine learning capability that enables researchers to perform advanced analysis of their imaging samples across multiple microscopy methods.

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