![](/images/stories/virtuemart/product/in carta example.jpg)
Flexi-Protocol application allows to create custom analysis protocols of various complexity by adding as many analysis steps is needed. Each analysis step can contain image pre-processing and object mask post-processing operation to better adapt to a specific assay. Redesigned analysis and image viewer panes can be expanded or collapsed depending on where focus is needed.
SINAP is a module that uses deep learning algorithms to improve accuracy and reliability of high-content screening assays at the first step in the analysis pipeline—segmentation. It provides better object detection than traditional image analysis methods. Deep learning models can be easily tailored within a user-friendly tool, so that any novel biological objects can be segmented efficiently. Quantitative information extracted from segmented objects is more accurate, so errors are not propagated down the analysis pipeline.
With SINAP, Segmentation Is Not A Problem!
IN Carta® Phenoglyphs™ Software Module uses a unique combination of unsupervised and supervised machine learning to quantify phenotypical changes. Using many hundreds of cellular features that can be analyzed simultaneously, a comprehensive phenotypic profile is created and can be applied throughout an entire screening workflow. This multivariate approach to classification provides accurate characterization of object populations allowing users to resolve subtle phenotypic changes induced by drug treatment or genetic modification. It can be utilized across many biological targets including organoids, cells, spheroids, and more.
Guided workflows and scalable batch processing increase productivity and reduce time to answer. Experiments can be set up quickly and analysis of multiple wells is run in parallel.
Machine learning helps you leverage more information and increase accuracy in the analysis of high-content screening data to enable new discoveries with confidence.
Modern user experience and cutting-edge technology minimizes the software learning curve and removes barriers to productivity.
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.
Browse to a parent directory and populate your worklist with image datasets of interest or simply use search to find them.
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.
Browse and review images from experiments, create image analysis protocols of different complexity and add on-demand data classification. Visualize analysis results using 360 ̊ data linking among images, data table and charts.
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.
Forgalmazott termékeink gyártói - keressen gyártó szerint a logóra kattintva