3D Cell Model Landing Page

Add another dimension to your research with end-to-end solutions for 3D imaging and analysis

Three-dimensional (3D) cell models are more physiologically relevant than two-dimensional cell cultures, and they more closely represent the tissue microenvironments, cell-to-cell interactions, and biological processes that occur in vivo.

Overcome the challenges of 3D imaging, and fully leverage the power of 3D cell models by increasing throughput, improving data quality, and generating actionable data faster.

Our solutions include:

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ImageXpress Confocal HT.ai system

Powerful multi-laser light sources, a deep tissue penetrating confocal disk module, water immersion objectives and modern machine learning analysis software.

High intensity laser light source: Capture images faster with shorter exposure times. Multiplex your experiments with 7 lasers and 8 imaging channels.
Multiple imaging modes: The system offers phase contrast and brightfield label-free imaging, widefield and confocal fluorescent imaging with water immersion optics as a standard option.
IN Carta Image Analysis Software: Leverages machine learning to improve the accuracy and robustness of high-content image analysis, delivering data insights that other technologies miss. Reduces the complexity of image analysis with intuitive guided workflows in a modern user interface.

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Modern machine learning, high-content image analysis software

Provides robust, quantitative results from complex biological images and datasets

AI-powered data analytics: Leverage the power of machine learning without being a data scientist. Identify and quantify phenotypic changes in a user-friendly workflow. Explore your data and reveal insights from complex datasets. Find novel and unexpected phenotypes with a few mouse clicks.
3D analysis: The Custom Module Editor’s 3D application provides unprecedented flexibility in segmenting complex biological structures. Image datasets can be acquired in 3D or 4D (timelapse 3D) and tailored image analysis routines can be developed within a guided workflow.
Deep learning: Improve specificity of your image analysis workflows by utilizing the SINAP module. SINAP relies on deep learning-based image analysis, resulting in robust segmentation for virtually any biological structure.