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examples.html
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---
redirect_from: "/examples.shtml"
---
<!DOCTYPE html>
<html>
<head>
<title>
CellProfiler example pipelines and utlities
</title>
<meta content="text/html; charset=utf-8" http-equiv="Content-Type">
<link rel="stylesheet" href="stylesheets/application.css">
<style media="all" type="text/css">
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<div id="content">
<h1>
Examples
</h1>
<p>
The best way to learn how to use CellProfiler and CellProfiler
Analyst is to download our examples and try it out!
</p>
<h2>
<a id="cp_examples" name="cp_examples">CellProfiler example images
and pipelines</a> <span style="font-size:75%">(jump to <a href=
"#cpa_examples">CellProfiler Analyst example</a>)</span>
</h2>
<div style="margin-left:3em">
<h3>
How do I get started?
</h3>
<p style="clear:both">
Download example images along with pipelines so you can get
immediate hands-on experience in using CellProfiler.
</p>
<ol>
<li>Select an example from the pipeline list below where the cell
type (or object type) resembles yours. You can move your mouse over
an image below to see an example of the CellProfiler analysis, or
click to see an expanded view.
</li>
<li>Download the example images and pipeline from the list below
and run it in CellProfiler to see how it works.
</li>
<li>Try the pipeline on your own images.
</li>
<li>Adjust the pipeline to identify objects properly in your
images. This most often includes changing the size range of the
objects. See the <a href="tutorials.html">Tutorials</a> page for
step by step instructions.
</li>
<li>Still stuck? See if your question has been answered on the
<a href="http://forum.cellprofiler.org">forum</a>.
</li>
</ol>
Please note that each example links to a compressed ZIP file
containing the following:
<ol>
<li>CellProfiler pipelines, in the 2.1.0 version (.cppipe) formats.
</li>
<li>Example images which are to be used as input for the pipeline.
</li>
</ol>
</div>
<div style="margin-left:3em">
<h2>
Table of contents
</h2>
<table align="center" border="1">
<tr>
<th rowspan="4">
Basic Pipelines
</th>
<td>
<a href="#HumanCells">Human cells</a>
</td>
</tr>
<tr>
<td>
<a href="#FruitFlyCells">Fruit fly cells</a>
</td>
</tr>
<tr>
<td>
<a href="#Tumors">Tumors</a>
</td>
</tr>
<tr>
<td>
<a href="#Comet">Comet assay</a>
</td>
</tr>
<tr>
<th rowspan="7">
Specialized Pipelines
</th>
<td>
<a href="#PercentPositive">Cell/particle counting, and scoring
the percentage of stained objects</a>
</td>
</tr>
<tr>
<td>
<a href="#YeastColonies">Yeast colony classification</a>
</td>
</tr>
<tr>
<td>
<a href="#YeastPatch">Yeast patch identification</a>
</td>
</tr>
<tr>
<td>
<a href="#TissueNeighbors">Tissue Neighbors</a>
</td>
</tr>
<tr>
<td>
<a href="#Wound">Wound Healing</a>
</td>
</tr>
<tr>
<td>
<a href="#IlluminationCorrection">Illumination Correction</a>
</td>
</tr>
<tr>
<td>
<a href="#Colocalization">Colocalization</a>
</td>
</tr>
<tr>
<th rowspan="3">
Pipelines using the WormToolbox
</th>
<td>
<a href="#UntangleWorms">Untangle worms</a>
</td>
</tr>
<tr>
<td>
<a href="#StraightenWorms">Straighten worms and extract
intensity measurements using a low-resolution atlas</a>
</td>
</tr>
<tr>
<td>
<a href="#UntangleWormsBright-field">Untangle worms and make
measurements bright-field staining pattern phenotype</a>
</td>
</tr>
<tr>
<th rowspan="5">
More Advanced Pipelines
</th>
<td>
<a href="#SBS_Vitra_CNT">Human cytoplasm-nucleus translocation
assay (SBS Vitra)</a>
</td>
</tr>
<tr>
<td>
<a href="#SBS_Bioimage_CNT">Human cytoplasm-nucleus
translocation assay (SBS Bioimage)</a>
</td>
</tr>
<tr>
<td>
<a href="#Speckles">Speckle Counting</a>
</td>
</tr>
<tr>
<td>
<a href="#Tracking">Object Tracking and Metadata Management</a>
</td>
</tr>
<tr>
<td>
<a href="#InSitu">Sequencing RNA molecules <i>in situ</i>
combining CellProfiler with ImageJ plugins</a>
</td>
</tr>
<tr>
<th rowspan="3">
File Utilities
</th>
<td>
<a href="#InvertForPrinting">Invert For Printing</a>
</td>
</tr>
<tr>
<td>
<a href="#ColorToGray">Color To Gray</a>
</td>
</tr>
<tr>
<td>
<a href="#FileConvert">Convert Image File Format</a>
</td>
</tr>
<tr>
<th>
Published Pipelines
</th>
<td>
<a href="#PublishedPipelines">Published Pipelines</a>
</td>
</tr>
</table>
</div>
<div style="margin-left:3em">
<table border="0">
<tr>
<td colspan="2">
<h3>
Basic Pipelines
</h3>
These pipelines are made for simple cellular and tissue image
assays, and include some basic measurements.
</td>
</tr>
<!-- Example Human cells-->
<tr>
<td valign="top">
<ul>
<li>
<a id="HumanCells" name="HumanCells"><span style=
"font-weight:bold">Human cells:</span></a> Human HT29 cells
are fairly smooth and elliptical. This pipeline
demonstrates how to accurately identify these cells and how
to measurements cellular parameters such as morphology,
count, intensity and texture.<br>
<a href="http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExampleHumanImages.zip"
onclick=
"ga('send', 'event', 'BasicPipeline', 'Downoad Human Cells')"
title="Human HT29 Cells Analysis">[Download]</a> (0.3 MB)
</li>
</ul>
</td>
<td valign="center">
<img alt="Basic CellProfiler pipeline Human HT29 Cell example"
border="0" class="exampleImage" height="128" id="HumanCells"
name="HumanCells" onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/HumanNuclei.jpg','','width=512,height=512')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('HumanCells','','http://d1zymp9ayga15t.cloudfront.net/images/HumanColorNucleism.jpg',1)"
src="http://d1zymp9ayga15t.cloudfront.net/images/HumanNuclei.jpg" style="clear:left">
</td>
</tr>
<!-- Example fruit flies-->
<tr>
<td>
<ul>
<li>
<a id="FruitFlyCells" name="FruitFlyCells"><span style=
"font-weight:bold">Fruit fly cells:</span></a> In comtrast
to the HT29 cells, Drosophila Kc167 cells are a highly
textured and clumpy cell type. This pipeline demonstrates
how to identify these clumpy cells and obtain
morphological, intensity and texture measurements.<br>
<a href="http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExampleFlyImages.zip"
onclick=
"ga('send', 'event', 'BasicPipeline', 'Downoad Fruit Flies')"
title=
"Fruit Fly Cell Biological Image Analysis">[Download]</a>
(4 MB)
</li>
</ul>
</td>
<td valign="center">
<img alt=
"Basic CellProfiler pipeline Fruit Fly Drosophilia Kc167 Cells example"
border="0" class="exampleImage" height="128" id="FruitFlyCells"
name="FruitFlyCells" onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/FruitflyImg.jpg','','width=479,height=435')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('FruitFlyCells','','http://d1zymp9ayga15t.cloudfront.net/images/Fruitfly-coded.jpg',1)"
src="http://d1zymp9ayga15t.cloudfront.net/images/FruitflyImg.jpg">
</td>
</tr>
<!-- Example Tumor -->
<tr>
<td valign="top">
<ul>
<li>
<a id="Tumors" name="Tumors"><span style=
"font-weight:bold">Tumors:</span></a> A simple pipeline
that identifies and counts tumors in a mouse lung, and then
measures their size.<br>
<a href="http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExampleTumorImages.zip"
onclick=
"ga('send', 'event', 'BasicPipeline', 'Downoad Tumor')"
title="Tumor Cell Analysis Mouse Lung">[Download]</a> (0.9
MB)
</li>
</ul>
</td>
<td valign="center">
<img alt=
"Basic Cellprofiler pipeline mouse lung Tumor Cell Example"
border="0" class="exampleImage" height="128" id="TumorCells"
name="TumorCells" onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/ExampleTumorImg.png','','width=400,height=300')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('TumorCells','','http://d1zymp9ayga15t.cloudfront.net/images/ExampleTumorID.png',1)"
src="http://d1zymp9ayga15t.cloudfront.net/images/ExampleTumorImg.png" style="clear:left">
</td>
</tr>
<!-- Example Comet -->
<tr>
<td valign="top">
<ul>
<li>
<a id="Comet" name="Comet"><span style=
"font-weight:bold">Comet assay</span></a> This is a simple
example of a DNA damage assay using single cell gel
electrophoresis. Here, the measurement of interest is the
length and intensity of the comet tail. Also, illumination
correction is used to reduce background flourescence prior
to measurement. Also shown is a silver-stained comet
example in which the percentage of DNA contained in the
tail is calculated.<br>
<a href="http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExampleCometAssay.zip"
onclick=
"ga('send', 'event', 'BasicPipeline', 'Downoad Comet')">[Download]</a>
(0.4 MB)
</li>
</ul>
</td>
<td valign="center">
<img alt=
"Basic CellProfiler pipeline Comet tail DNA damage assay example"
border="0" class="exampleImage" height="128" id="Comet" name=
"Comet" onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/ExampleCometImg.png','','width=400,height=300')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('Comet','','http://d1zymp9ayga15t.cloudfront.net/images/ExampleCometID.png',1)" src=
"http://d1zymp9ayga15t.cloudfront.net/images/ExampleCometImg.png" style="clear:left">
</td>
</tr>
<tr>
<td colspan="2">
<h3>
Specialized pipelines
</h3>
In addition to cellular object and feature identification,
these pipelines include some of the more specialized modules in
CellProfiler for image pre-processing or measurement.
</td>
</tr>
<!-- Percent Positive -->
<tr>
<td valign="top">
<ul>
<li>
<a id="PercentPositive" name="PercentPositive"><span style=
"font-weight:bold">Cell/particle counting, and scoring the
percentage of stained objects:</span></a> CellProfiler is
commonly used to count cells or other objects as well as
percent-positives, by measuring the per-cell staining
intensity. This pipeline shows how to do both of these
tasks, and demonstrates how various modules may be used to
accomplish the same result.<br>
<a href=
"http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExamplePercentPositive.zip"
onclick=
"ga('send', 'event', 'Special', 'Downoad PercentPositive')">
[Download]</a> (0.2 MB)<br>
</li>
</ul>
</td>
<td valign="center">
<img alt=
"Specialized CellProfiler pipeline Percent Positive count per-cell stain intensity example"
border="0" class="exampleImage" height="128" id=
"PercentPositive" name="PercentPositive" onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/ExamplePercentPosImg.png','','width=235,height=235')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('PercentPositive','','http://d1zymp9ayga15t.cloudfront.net/images/ExamplePercentPosID.png',1)"
src="http://d1zymp9ayga15t.cloudfront.net/images/ExamplePercentPosImg.png" style="clear:left"><br>
</td>
</tr>
<!-- Example Colonies -->
<tr>
<td valign="top">
<ul>
<li>
<a id="YeastColonies" name="YeastColonies"><span style=
"font-weight:bold">Yeast colony classification:</span></a>
This pipeline demonstrates how to classify and count
objects on the basis of their measured features. The
example identifies uniformly round objects, in this case,
yeast colonies growing on a dish. The pipeline also shows
how to load a template and align it to a cropped image, as
well as how to use illumination correction to subtract for
background illumination.<br>
<a href=
"http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExampleYeastColonies_BT_Images.zip"
onclick=
"ga('send', 'event', 'Special', 'Downoad YeastColony')">[Download]</a>
(0.2 MB)<br>
<a href=
"http://d1zymp9ayga15t.cloudfront.net/papers/85-Bray_CurrentProtocols_2015.pdf"
onclick=
"ga('send', 'event', 'Special', 'Download YeastColony PDF')">
[Tutorial]</a>
</li>
</ul>
</td>
<td valign="center">
<img alt=
"Specialized CellProfiler pipeline identify Yeast Colony Classification example"
border="0" class="exampleImage" height="128" id="YeastColonies"
name="YeastColonies" onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/YeastCrop.jpg','','width=235,height=235')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('YeastColonies','','http://d1zymp9ayga15t.cloudfront.net/images/YeastCropID.jpg',1)"
src="http://d1zymp9ayga15t.cloudfront.net/images/YeastCrop.jpg" style="clear:left"><br>
</td>
</tr>
<!-- Example Yeast patch -->
<tr>
<td valign="top">
<ul>
<li>
<a id="YeastPatch" name="YeastPatch"><span style=
"font-weight:bold">Yeast patch identification:</span></a>
This pipeline identifies patches of yeast growing in a 96
well plate, serving as an introduction to the grid
defintion and identification modules.<br>
<a href=
"http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExampleYeastPatchImages.zip"
onclick=
"ga('send', 'event', 'Special', 'Downoad YeastPatchImages')">
Download]</a> (0.4 MB)
</li>
</ul>
</td>
<td valign="center">
<img alt=
"Specialized CellProfiler pipeline identify Yeast Patch example"
border="0" class="exampleImage" height="128" id="YeastPatch"
name="YeastPatch" onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/ExampleYeastPatch.png','','width=235,height=235')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('YeastPatch','','http://d1zymp9ayga15t.cloudfront.net/images/ExampleYeastPatchID.png',1)"
src="http://d1zymp9ayga15t.cloudfront.net/images/ExampleYeastPatch.png" style="clear:left"><br>
</td>
</tr>
<!--Grid of spots-->
<!--
<tr>
<td valign="top"">
<ul><li><span style="font-weight:bold">Annotation: </span>
Example labeling a cell microarray with an annotated grid.
<a href="http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExampleGridImages.zip">[Download]</a></li></ul>
</td>
-->
<!-- Tissue neighbors-->
<tr>
<td valign="top">
<ul>
<li>
<a id="TissueNeighbors" name="TissueNeighbors"><span style=
"font-weight:bold">Tissue Neighbors:</span></a> Tissue
samples often have irregularly shaped cells with adjacent
edges. This pipeline shows how to input a color tissue
image, split it into its component channels, and then
identify individual cells from a particular stain and
record the number of neighbors that each cell has.<br>
<a href=
"http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExampleNeighborsImages.zip"
onclick=
"ga('send', 'event', 'Special', 'Downoad TissueNeighbors')">
(0.1 MB)</a>
</li>
</ul>
</td>
<td valign="center">
<img alt=
"Specialized CellProfiler pipeline color Tissue image identify example"
border="0" class="exampleImage" height="128" id=
"TissueNeighbors" name="TissueNeighbors" onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/TissueNeighbors.jpg','','width=531,height=426')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('TissueNeighbors','','http://d1zymp9ayga15t.cloudfront.net/images/Clones1colorneighbors.jpg',1)"
src="http://d1zymp9ayga15t.cloudfront.net/images/TissueNeighbors.jpg" style="clear:left">
</td>
</tr>
<!-- Wound healing-->
<tr>
<td valign="top">
<ul>
<li>
<a id="Wound" name="Wound"><span style=
"font-weight:bold">Wound Healing:</span></a> In this
example, cells are grown as a tissue monolayer. Rather than
identifying individual cells, this pipeline quantifies the
area occupied by the tissue sample.<br>
<a href=
"http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExampleWoundHealingImages.zip"
onclick=
"ga('send', 'event', 'Special', 'Downoad Wound')">[Download]</a>
(1.1 MB)
</li>
</ul>
</td>
<td valign="center">
<img alt=
"Specialized Cellprofiler pipeline quantify area Tissue Monolayer example"
class="exampleImage" height="128" id="Wound" name="Wound"
onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/WOUND-IMG.gif','','width=255,height=170')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('Wound','','http://d1zymp9ayga15t.cloudfront.net/images/WOUND-ANALYSIS.gif',1)" src=
"http://d1zymp9ayga15t.cloudfront.net/images/WOUND-IMG.gif">
</td>
</tr>
<!--Illumination correction-->
<tr>
<td valign="top">
<ul>
<li>
<a id="IlluminationCorrection" name=
"IlluminationCorrection"><span style=
"font-weight:bold">Illumination Correction:</span></a>
Illumination correction is often important for both
accurate segmentation and for intensity measurements. This
example shows how the CorrectIlluminationCalculate and
CorrectIlluminationApply modules are used to compensate for
the non-uniformities in illumination often present in
microscopy images.<br>
<a href=
"http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExampleIlluminationCorrection.zip"
onclick=
"ga('send', 'event', 'Special', 'Downoad IlluminationCorrection')">
[Download]</a> (14.9 MB)
</li>
<li style="list-style: none">
<a href=
"http://d1zymp9ayga15t.cloudfront.net/content/ExampleIlluminationCorrection_Tutorial.pdf"
oonclick=
"ga('send', 'event', 'Special', 'Downoad IlluminationCorrectionPDF')">
[Tutorial]</a>
</li>
</ul>
</td>
<td valign="center">
<img alt=
"Specialized Cellprofiler pipeline Illumination Correction example"
class="exampleImage" height="128" id="IlluminationCorrection"
name="IlluminationCorrection" onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/ExampleIlluminationCorrection_Orig.png','','width=170,height=170')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('IlluminationCorrection','','http://d1zymp9ayga15t.cloudfront.net/images/ExampleIlluminationCorrection_Corr.png',1)"
src="http://d1zymp9ayga15t.cloudfront.net/images/ExampleIlluminationCorrection_Orig.png">
</td>
</tr>
<!--Colocalization-->
<tr>
<td valign="top">
<ul>
<li>
<a id="Colocalization" name="Colocalization"><span style=
"font-weight:bold">Colocalization:</span></a> Measuring the
colocalization between fluorescently labeled molecules is a
widely used approach to measure the degree of spatial
coincidence and potential interactions among subcellular
species (e.g., proteins). This example shows how the object
identifcation and RelateObjects modules are used to measure
the degree of overlap between two fluorescent channels.<br>
<a href=
"http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExampleColocalization__.zip"
onclick=
"_gaq.push(['_trackEvent', 'SpecialityPipeline', 'Download', 'ColocalizationDownload']);">
[Download]</a> (3.7 MB)
</li>
<li style="list-style: none">
<a href="http://d1zymp9ayga15t.cloudfront.net/content/Example_Colocalization_Tutorial.docx"
onclick=
"_gaq.push(['_trackEvent', 'SpecialityPDF', 'Download', 'ColocalizationPDF']);">
[Tutorial]</a>
</li>
</ul>
</td>
<td valign="center">
<img alt=
"Specialized CellProfiler Colocalization Spation Coincidence Subcellular example"
class="exampleImage" height="128" id="Colocalization" name=
"Colocalization" onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/ExampleColocalization_Orig.png','','width=170,height=170')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('Colocalization','','http://d1zymp9ayga15t.cloudfront.net/images/ExampleColocalization_Masked.png',1)"
src="http://d1zymp9ayga15t.cloudfront.net/images/ExampleColocalization_Orig.png">
</td>
</tr>
<tr>
<td colspan="2">
<h3>
<a id="WormToolbox" name="WormToolbox">Pipelines using the
WormToolbox</a>
</h3>
These pipelines have been developed for high-throughput screens
on <i>C. elegans</i> and extract measurements on a per-worm
basis.<br>
<p style="font-size:small;font-style:italic;margin-left:27px;">
The <a href="http://www.cellprofiler.org/wormtoolbox/">Worm
Toolbox</a> page has further details on this workflow, as
well as video tutorials, pipelines and image data in addition
to those described below. (from C Wählby <i>et al.
<i>Methods</i>, 2014)<br>
The <a href="http://www.broadinstitute.org/bbbc">BBBC</a>
also has <i>C. elegans</i> sample images and information, as
well as assay "ground truth" of various kinds.</i>
</p>
</td>
</tr>
<!--Untangle worms-->
<tr>
<td valign="top">
<ul>
<li>
<a id="UntangleWorms" name="UntangleWorms"><span style=
"font-weight:bold">Untangle worms:</span></a> In this
pipeline, we identify individual worms and extract shape
and intensity measurements. Worm untangling requires a worm
model, which is provided together with the pipeline. If
adjusting the pipeline to fit your own data, worm detection
will likely improve by creating a new worm model based on
your own image data.<br>
<a href=
"http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExamplePipelineUntangle.zip"
onclick=
"_gaq.push(['_trackEvent', 'WormPipeline', 'Download', 'UntangleDownload']);">
[Download]</a> (1.3 MB)
</li>
</ul>
</td>
<td valign="center">
<img alt=
"Worm Toolbox CellProfiler Shape Intensity Untangle Worms CellProfiler"
class="exampleImage" height="128" id="Untangle" name="Model"
onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/ExampleUntangleInput.gif','','width=382,height=396')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('Untangle','','http://d1zymp9ayga15t.cloudfront.net/images/ExampleUntangleOutput.gif',1)"
src="http://d1zymp9ayga15t.cloudfront.net/images/ExampleUntangleInput.gif">
</td>
</tr>
<!--Straighten worms-->
<tr>
<td valign="top">
<ul>
<li>
<a id="StraightenWorms" name="StraightenWorms"><span style=
"font-weight:bold">Straighten worms and extract intensity
measurements using a low-resolution atlas:</span></a> Once
worms are untangled, this pipeline shows how they can be
straightened and aligned with a low-resolution worm atlas
to extract localized intensity measurements and compare
patterns of reporter signals. Included are steps for
identifying secondary objects (fluorescent marker signals)
and relating these objects to individual worms, enabling
count of signals on a per-worm basis.<br>
<a href=
"http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExamplePipelineStraighten.zip"
onclick=
"_gaq.push(['_trackEvent', 'WormPipeline', 'Download', 'StraightenDownload']);">
[Download]</a> (968 KB)
</li>
</ul>
</td>
<td valign="center">
<img alt="Worm Toolbox CellProfiler Straighten Worms example"
class="exampleImage" height="128" id="Model" name="Straighten"
onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/ExampleStraightenInput.gif','','width=530,height=384')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('Straighten','','http://d1zymp9ayga15t.cloudfront.net/images/ExampleStraightenOutput.gif',1)"
src="http://d1zymp9ayga15t.cloudfront.net/images/ExampleStraightenInput.gif">
</td>
</tr>
<!--Create worm model-->
<tr>
<td valign="top">
<ul>
<li>
<a id="CreateModel" name="CreateModel"><span style=
"font-weight:bold">Create your own worm model:</span></a>
The UntangleWorms module has an "Untangle" mode
and a "Train" mode. This pipeline describes how
the "Train" mode is used to create a worm model.
Training consists of providing a large number of images of
worms that are representative of the worm variation within
the population, and that do not touch or overlap. Note that
this example download includes only two images and will not
result in a good model, as it will not be representative of
all possible variations of the worm shapes. We recommend
using at least 60 worms to create a model.<br>
<a href=
"http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExamplePipelineCreateModel.zip"
onclick=
"_gaq.push(['_trackEvent', 'WormPipeline', 'Download', 'CreateDownload']);">
[Download]</a> (1.6 MB)
</li>
</ul>
</td>
<td valign="center">
<img alt=
"Worm Toolbox Cellprofiler Create Untangle Train Model Worm example"
class="exampleImage" height="128" id="CreateModel" name="Model"
onclick=
"MM_openBrWindow('http://d1zymp9ayga15t.cloudfront.net/images/ExampleCreateModelInput.gif','','width=390,height=463')"
onmouseout="MM_swapImgRestore()" onmouseover=
"MM_swapImage('CreateModel','','http://d1zymp9ayga15t.cloudfront.net/images/ExampleCreateModelOutput.gif',1)"
src="http://d1zymp9ayga15t.cloudfront.net/images/ExampleCreateModelInput.gif">
</td>
</tr>
<!--Bright-field untangling-->
<tr>
<td valign="top">
<ul>
<li>
<a id="UntangleWormsBright-field" name=
"UntangleWormsBright-field"><span style=
"font-weight:bold">Untangle worms and make measurements
bright-field staining pattern phenotype:</span></a> This
pipeline detects individual worms by worm untangling and
finds sub-objects (fatty regions stained with oil red O)
within the worms. Using bright-field data only, it detects
fatty regions by intensity thresholding in a single image
channel and relates the fatty regions to individual worms.
This enables detection of rare phenotypes in heterogeneous
populations, phenotypes that would be missed if population
averages were observed. More data can be found on the
<a href="http://www.broadinstitute.org/bbbc">BBBC</a>.<br>
<a href=
"http://d1zymp9ayga15t.cloudfront.net/content/Examplezips/ExamplePipelineOilRedO.zip"
onclick=
"_gaq.push(['_trackEvent', 'WormPipeline', 'Download', 'UntangleDownload']);">
[Download]</a> (852 KB)
</li>
</ul>
</td>