Deep Learning Object Segmentation
Complete object detection powered by Cellpose
Aivia 11 incorporates state-of-the-art deep learning models by Cellpose (Stringer, 2021)  for object detection. We are offering AI access for all with four new Cellpose-integrated analysis recipes for 2D and 3D object segmentations - no knowledge of Python scripting or training deep learning models necessary.
The models are highly adaptable to various imaging modalities and staining conditions. Whether your imaging experiment involves DIC systems or fluorescent membrane stains, the object segmentation recipes powered by Cellpose enable you to get robust and reproducible segmentation every time.
Use Cellpose's powerful object detection deep learning models
No knowledge of Python scripting or deep learning model training needed
Leverage existing Aivia tools for your analysis routine
In Aivia 9, we were the first commercially-available software to offer AI-powered object segmentation with Cellpose by the way of Python scripts. By integrating Cellpose into our existing infrastructure, Aivia 11 makes it easier to deploy deep learning cell segmentation in your workflow and get results up to 80% faster.
 Stringer C, Wang T, Michaelos M, Pachitariu M. Cellpose: a generalist algorithm for cellular segmentation. Nature Methods. 18: 100-106. (2021)
Analyze your entire experiment
Your experiments can have multiple test conditions at the same time and your analysis software should let you analyze them all at once. In Aivia 11, we are introducing several features that allow you to visualize, explore, and analyze your multi-well experiments and accelerate insights creation on a single platform.
Starting with your imaging experiment, Aivia 11's new Experiment Explorer allows you to import Leica multi-well data into Aivia. You can explore images from individual wells or imaging experiments from the Multi-well Navigator and assign labels to annotate the experiment conditions for your well plates.
Import and explore your entire multi-well experiment with intuitive Navigator
Define experimental conditions for downstream analysis
Export results to CytoMAP for further data exploration
Support for Leica's multi-well data format from the MICA imaging system and more
You can analyze your image using Aivia's built-in tools on a single FOV and build an analysis pipeline using the new Workflows tool. The analysis workflow you built can then be batch applied to your entire imaging experiment - or just on select wells with your annotated conditions.
The analysis results collected from batch applying the workflow can be exported to CytoMAP (Stoltzfus, 2020)  for further data exploration. Leverage CytoMAP's capabilities (such as dimension reduction) to accelerate insight creation from your imaging experiment, speeding up your route to publication.
 Stoltzfus CR, Filipek J, Gern BH, et al. CytoMAP: a spatial analysis toolbox reveals features of myeloid cell organization in lymphoid tissues. Cell reports. 31(3): 107523.