IMAGE ANALYSIS SUPPORT
CellProfiler™, Fiji/ImageJ, KNIME, QuPath, Ilastik, custom Python Scripts
Wako Automation Image Analysis Services
Free Image Analysis Service
CellProfiler™, Fiji/ImageJ, KNIME, QuPath, Ilastik, custom Python image analysis scripts
CellProfiler is cell image analysis software designed for biologist. It was developed and is maintained by Dr. Anne Carpenter’s lab at the Broad Institute of Harvard and MIT. CellProfiler can be downloaded here: https://cellprofiler.org. CellProfiler is open source and free to download and use.
Wako Automation is working with Dr. Carpenter’s lab in an effort to provide support to users of CellProfiler. Once you download CellProfiler try out some example pipelines and tutorials located here: https://cellprofiler.org/examples. If you need additional assistance please visit the online forum for help: https://forum.image.sc/tag/cellprofiler. Scientists from the CellProfiler community, Dr. Carpenter’s lab and Wako Automation continuously monitor the forum and provide answers to questions. If you need additional assistance, Wako Automation provides a number of services to help the imaging community.
- CellProfiler training classes – A Fujifilm application scientists can provide a half day or more of training using a mix of example datasets as well as your own in house data to help you understand how to use CellProfiler and get you on your way to building optimized CellProfiler pipelines/workflows designed to quantify images so you can advance your specific research projects.
- CellProfiler pipeline design – Some image analysis pipelines/workflows may be quite complex, in other instances your lab may be overwhelmed with imaging data and may just need help to get you 90% of the way there, or Fujifilm can build you a finalized pipeline. This service is designed to help customers outsource CellProfiler pipeline/workflow design and simultaneously teach scientists how to become CellProfiler experts. Scientists simply upload a few sample images for a specific project (positive control, negative control, and sample images), along with an explanation of what needs to be quantified. From these images and our application scientists will develop a CellProfiler pipeline/workflow to get you the results for your experiment. This pipeline is sent back to our customer who can then work with our application scientist to finalize an optimized pipeline. This process not only gets you a jump start on one of the most difficult aspects of running an imaging experiment, but also helps train you to become an CellProfiler expert.
- Fiji/ImageJ, KNIME, QuPath, Ilastik, custom Python image analysis scripts – In addition to working with CellProfiler, Fujifilm Wako Automation can provide training and analysis assistance for Fiji/ImageJ, KNIME, Ilastik and QuPath. If your application requires a fully custom solution we can also provide custom Python scripts to get you the results you are looking for.
The best way to contact us to learn more about any of these services is via our online request form: https://www.wakoautomation.com/contact-us. We look forward to hearing from you.
Below are a number of free CellProfiler pipeline/workflow tutorials, created by our applications scientist, to assist in a broad range of image analysis challenges. Download the tutorials and see how our application scientists use CellProfiler to solve these challenges. Check back every so often as we will continue to add additional pipeline/workflow tutorials.
Getting Started with CellProfiler, the Basics
A basic guide for scientists who are using CellProfiler for the first time. Please download and review this guide and then download and follow the tutorials. If you already have CellProfiler experience, skip this guide and go right to the tutorials.
Download Tutorial »
Segment Fibroblasts
This pipeline illustrates techniques used to segment spindle shaped fibroblasts from a three channel image using basic CellProfiler modules that enable image thresholding adjustments and smoothing parameters. In addition, colocalization of two of the channels from the segmented objects is reported.
Image: Multichannel image (DAPI, Actin, Myosin)
Download Tutorial »
Segment Microglia
Aim: To segment microglia
This pipeline illustrates the segmentation of complete microglia with dendrites using CellProfiler’s™ EnhanceSuppress features.
Image: 2 channel image (DAPI & GFP)
Download Tutorial »
3D Segmentation of Tumor Cells
This pipeline illustrates how CellProfiler can be used to perform 3D analysis on confocal images of cells and nuclei.
Image: two channel confocal image
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Download Tutorial »
Segmentation of Cells in Tissue with High Background
Aim: Segment cells within a tissue image with high background.
This pipeline utilizes CellProfiler’s EnhanceOrSuppressFeatures module to suppress high background before segmentation.
Image: A single tissue image.
Download Tutorial »
Using the MaskObjects Function With A Manually Drawn or Imported Region Of Interest
Images: One multi-colored neuronal image and a binary image of a predefined mask representing the Region Of Interest (ROI).
Download Tutorial »
Seed counting (Agriculture Application)
This pipeline illustrates CellProfiler’sTM ability to identify the local maxima from a standard photograph. By identifying local maxima corn kernels can be recognized and counted.
Image: Single color image of an ear of corn.
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Download Tutorial »
Segmentation and Classification of Individual Oocytes Based on Size
This pipeline illustrates how to create a mask of the region of interest (in this case the tissue), to isolate a colony of oocytes, identify and segment individual oocytes, and then filter them based on size.
Image: Single color image
Download Tutorial »
Segmenting a Viral Plaque from a Brightfield Image
Aim:
This example pipeline shows the segmentation of a large region, in this case a viral plaque, from a brightfield image.
Image: A Single Differential Interference Contrast (DIC) Image
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Saving each Segmented Cell as an Individual Mask
Image: Single image with nuclei and cell signal
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Using the Groups Module to Analyze Data by Well
