CellPathfinder

CellPathfinder, High Content Analysis Software

Leverage industry leading technology to optimize cell imaging processes.

A powerful tool for high content analysis systems, the software analyzes and digitizes complex high content imaging experiment data. From 3D culture systems to live imaging, users can easily access multiple evaluation systems, capitalizing on the software’s machine learning functions to dramatically increase target recognition and decrease slow turnarounds.

•    Intuitive interface guides users through processes
•    Machine learning continually improves process success
•    Provides abundant analysis functions to individualize research
•    Compatible with Total Solutions

Upcoming Events

CellPathfinder Resolves Difficulties

For screening

CellPathfinder resolves screening bottlenecks.

  • A specialized interface for inspecting multiple samples makes image comparison easy, improving efficiency
  • Advanced analysis using AI is possible through simple operation, even for beginners
  • Various graph creation functions and simple image and video creation, reducing hassles at the time of reporting

For cancer research and regenerative medicine screening

CellPathfinder provides leading HCA through proprietary analysis technology.

  • Label-free analysis of samples that you don’t want to stain is possible using Yokogawa’s proprietary image generation technology “CE Bright Field”
  • Newly-developed easy-to-use machine-learning (standard function) makes previously difficult phenomena detection easy
  • Detection of rare events (CTC, etc.) with high speed and high accuracy

 

Applications

Cell Imaging Software Applications

Details

Simplify workflow from images to analysis and graphs

1. Display image data

Display image data

・Easy to compare images between wells

 

2. Load and execute analysis protocol

 Load and execute analysis protocol

・Easy-to-understand graphical icons
・Choose a preset template for your analysis

 

3. Gating

Gating

・Specific populations can be extracted by gating the feature value data of recognized objects
・The extracted populations can be analyzed further

 

4. Make the graphs

Make the graphs

・Various graph options to visualize the results
・The link between graph and images enables quick visual check of images by clicking data points

 

5. To examine further details - list the profiles of interesting cells

To examine further details

・Images and numerical data can be collected by clicking cells

Yokogawa technology

Machine-learning

Machine-learning functionality allows for unbiased digitization in experiments evaluated through appearance.
Automated shape recognition can be performed by simply clicking on the shape you wish the software to learn.

Machine-learning

 

CE Bright Field(Contrast-enhanced Bright Field )

By using Yokogawa’s “CE-Bright Field” proprietary image creation technology, two types of images can be output from bright field images. The first is an image resembling a phase-difference image, created from a regular DPC (digital phase contrast) image, and is effective for cytoplasm recognition. The second is an image resembling a fluorescence image, effective for nuclear recognition.

CE Bright Field

Abundant analysis functions

3D analysis

・Analysis of Z-stack images in three-dimensional space. ・The volume and the location of objects in 3D space can be quantified.

3D analysis

 

Label-free Analysis

The recognition of cells without the use of labeling is possible using images created with CE Bright Field technology.
Time, cost and effects on cells due to fluorescent labeling are eliminated from phenotype analysis.

labelfree

 

Image Stitching*1

Tiled images are generated through image stitching and analyzed, allowing for accurate quantification.
Ideal for analysis spanning across fields, such as of spheroids, tissue sections and neurites.

Tiling

 

Manual Region definition*1

Manual region of analysis regions is possible for complex trends that are difficult to identify through automated image processing.
Morphology in the defined regions can be visualized, facilitating analysis.

Manual Region definition
Data provided by Dr. Yasuhito Shimada, Mie University Graduate School of Medicine

 

*1: Coming soon

Cell Recognition (Deep Area Finder)

High-accuracy recognition of targeted areas, such as cells and intracellular organelles.
This is effective when the accuracy of existing recognition techniques is not enough, and the expertise in image analysis is not available.

Original image

Original image

Recognition result

Recognition result

Cell Counts (Deep Cell Detector)

Intuitive cell counting
Detect cells without establishing a complicated image analysis protocol. Particularly effective for analyzing high-density cultured cells and bright field analysis.

Original image

Original image

Recognition result

Recognition result

Cell Classification (Deep Image Gate)

Classification of recognized cells into any grouping.
You can intuitively categorize complicated phenotypes without selecting feature quantities.

Classification of cell cycle (G1, Early S, SG2M) using the Fucci system

  • Added 0–6.8μM etoposide to HeLa cells with Fucci
  • 48-hours time lapse over 1 hour intervals at 10x; 488nm and 561nm
6.8uM Etoposide

6.8uM Etoposide

Control

Control

Ratio of cells in each cell cycle at each well.

Ratio of cells in each cell cycle at each well.

EC50/IC50 Calculation (Deep Image Response)

Evaluating whole images to calculate EC50/IC50 from positive/negative controls and concentration data.
Comprehensively analyzes complicated phenotypes without creating protocols for cell recognition and selecting any feature.

 

Dose response curve

Dose response curve

Total Solution - from Imaging to Analysis

Offering Total Solutions, from Measurement to Analysis Plate transport via robot, measurement using CellVoyager or CQ1, data management using CellLibrarian, and image analysis using CellPathfinder. We offer optimum combinations matched to users’ needs and budgets.

System

Large image: Click

Related products

CV8000 CV8000
  • Ultimate HCA system for high-quality imaging and high-throughput screening with water immersion objectives and multiple cameras
  • Built-in robot pipettor for kinetic assays
CQ1 CQ1
  • Benchtop size confocal system
  • Simple operation and automated image acquisition of many samples
  • Live cell imaging

※Data acquired in CellVoyager CV1000 are not supported.
※CellPathfinder system contains the software and the workstation.

System configuration

・Software
・Workstation
・Displays

Specifications of the workstation
Model: Dell Precision
CPU: Intel® Xeon
Memory:128 GB
HDD: System(C:) 4TB Storage, (D:) 4TB
OS: Windows® Microsoft Windows10 IoT Enterprise
GPU: System(C:) Quadro K620 or Quadro P620 (High-performance GPU is not selected.), Quadro RTX5000 (High-performance GPU is selected.)

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Resources

Overview:

PhenoVista Biosciences is the leading provider of custom, imaging-based, phenotypic assay services. With a collaborative and scientifically driven project design and management approach, PhenoVista has a proven track record of delivering high-quality data from robust and scalable assays. PhenoVista’s key advantage lies in the ability of their industry-trained scientists to combine world-class understanding of diverse biological systems with cutting-edge quantitative imaging to deliver clear, actionable output data.

Overview:

Applications: Colony Formation, Scratch Wound, Cytotoxicity, Neurite Outgrowth, Co-culture Analysis, Cell Tracking

Industries:
Application Note
Overview:

Fluorescent ubiquitination-based cell cycle indicator (Fucci) is a set of fluorescent probes which enables the visualization of cell cycle progression in living cells.

Industries:
Application Note
Application Note
Application Note
Application Note
Overview:

Cell stage categorized using FucciTime lapse imaging of Fucci-added Hela cells was conducted over 48 hrs at 1 hr intervals. Gating was performed based on the mean intensities of 488 nm and 561 nm for each cell. They were categorized into four stages, and the cell count for each was calculated.

Industries:
Application Note
Application Note
Overview:

The CQ1 confocal image acquisition mechanism with the distinctive CSU® unit has a function to sequentially acquire fine cell images along the Z-axis and capture information from the entire thickness of
cells which include heterogenic populations of various cell cycle stages. In addition, saved digital images can be useful for precise observation and analysis of spatial distribution of intracellular molecules.
The CQ1 capability to seamlessly analyze images and obtain data for things such as cell population statistics to individual cell morphology will provide benefits for both basic research and drug discovery
targetingM-cell cycle phase.

Overview:

List of Selected Publications : CV8000, CV7000, CV6000

Yokogawa Technical Report
Overview:

We have been developing a prototype of a genomic drug test support system using our CSU confocal scanner. This system administers chemical compounds that serve as potential drug candidates into living cells, which are the most basic components of all living organisms, records the changes in the amount and localization of target molecules inside cells with the CSU confocal scanner and a highly sensitive CCD camera, and processes and quantifies the captured high-resolution image data.

Yokogawa Technical Report
18.6 MB
Overview:

In this tutorial, we will learn how to perform cell tracking with CellPathfinder through the analysis of test images.

Overview:

In this tutorial, a method for analyzing ramified structure, using CellPathfinder, for the analysis of the vascular endothelial cell angiogenesis function will be explained.

Overview:

In this tutorial, we will learn how to perform time-lapse analysis of objects with little movement using CellPathfinder, through calcium imaging of iPS cell-derived cardiomyocytes.

Overview:

In this tutorial, we will observe the change in number and length of neurites due to nerve growth factor (NGF) stimulation in PC12 cells.

Overview:

In this tutorial, image analysis of collapsing stress fibers will be performed, and concentration-dependence curves will be drawn for quantitative evaluation.

Overview:

In this tutorial, we will identify the cell cycles G1-phase, G2/M-phase, etc. using the intranuclear DNA content.

Overview:

In this tutorial, spheroid diameter and cell (nuclei) count within the spheroid will be analyzed.

Overview:

In this tutorial, a method for analyzing ramified structure, using CellPathfinder, for the analysis of the vascular endothelial cell angiogenesis function will be explained.

Overview:

In this tutorial, using images of zebrafish whose blood vessels are labeled with EGFP, tiling of the images and recognition of blood vessels within an arbitrary region will be explained.

Overview:

In this tutorial, intranuclear and intracytoplasmic NFκB will be measured and their ratios calculated, and a dose-response curve will be created.

To download CellPathfinder, click here.

Downloads

Videos

Overview:

Yokogawa's CQ1 open platform integrates seamlessly with Advanced Solutions BioAssemblyBot® 400. With laboratory automation becoming a standard in research, Yokogawa's high content confocal system's ability to work with robots like Advanced Solutions' BioAssemblyBot® 400 is essential to advancing laboratory automation.

Overview:

In this webinar, Professor Jonny Sexton discusses a pipeline, developed in the Sexton lab, for the quantitative high-throughput image-based screening of SARS-CoV-2 infection to identify potential antiviral mechanisms and allow selection of appropriate drug combinations to treat COVID-19. This webinar presents evidence that morphological profiling can robustly identify new potential therapeutics against SARS-CoV-2 infection as well as drugs that potentially worsen COVID-19 outcomes.

Overview:

Dr. Sexton discusses high content screening for phenotypic-based drug discovery and development using Yokogawa technologies. This webinar presents the methodology behind acquiring good images that are able to leverage the three-dimensionality of different cell systems. His assays include 3D models such as organoids and spheroids.

In this webinar, you will discover:

  • How to identify when 2D or 3D methods are required to achieve desired results.
  • How to leverage your High Content Imaging Systems to get optimal signals and backgrounds.
  • Techniques that are used to improve cell observation yield and statistical distributions of morphological features.
Overview:

3D imaging experts from Yokogawa and Insphero have come together to provide helpful tips and tricks on acquiring the best 3D spheroid and organoid imaging. This webinar focuses on sample preparation, imaging, and analysis for both fixed and live cells in High Content Screening assays. The experts also discuss automated tools that can help researchers understand the large volume of data in these High Content Imaging Analysis Systems.

Overview:

3D imaging experts from Yokogawa and Insphero have come together to provide helpful tips and tricks on acquiring the best 3D spheroid and organoid imaging. This webinar focuses on sample preparation, imaging, and analysis for both fixed and live cells in High Content Screening assays. The experts also discuss automated tools that can help researchers understand the large volume of data in these High Content Imaging Analysis Systems.

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