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Merge pull request #53 from BodenmillerGroup/imctools2
Updates the example pipeline outline to CP4 and imctools v2
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| CellProfiler Pipeline: http://www.cellprofiler.org | ||
| Version:5 | ||
| DateRevision:406 | ||
| GitHash: | ||
| ModuleCount:12 | ||
| HasImagePlaneDetails:False | ||
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| Images:[module_num:1|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['This module will prepare ilastik stacks for the ilastik cell classification pipeline.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] | ||
| : | ||
| Filter images?:Images only | ||
| Select the rule criteria:and (extension does isimage) (directory doesnot containregexp "[\\\\/]\\.") | ||
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| Metadata:[module_num:2|svn_version:'Unknown'|variable_revision_number:6|show_window:False|notes:['No metadata.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] | ||
| Extract metadata?:Yes | ||
| Metadata data type:Text | ||
| Metadata types:{} | ||
| Extraction method count:1 | ||
| Metadata extraction method:Extract from file/folder names | ||
| Metadata source:File name | ||
| Regular expression to extract from file name:^(?P<filename>.*) | ||
| Regular expression to extract from folder name:(?P<Date>[0-9]{4}_[0-9]{2}_[0-9]{2})$ | ||
| Extract metadata from:All images | ||
| Select the filtering criteria:and (file does contain "") | ||
| Metadata file location:Elsewhere...| | ||
| Match file and image metadata:[] | ||
| Use case insensitive matching?:No | ||
| Metadata file name: | ||
| Does cached metadata exist?:No | ||
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| NamesAndTypes:[module_num:3|svn_version:'Unknown'|variable_revision_number:8|show_window:False|notes:['Here only _ilastik.tiff files are selected.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] | ||
| Assign a name to:Images matching rules | ||
| Select the image type:Grayscale image | ||
| Name to assign these images:DNA | ||
| Match metadata:[] | ||
| Image set matching method:Order | ||
| Set intensity range from:Image metadata | ||
| Assignments count:1 | ||
| Single images count:0 | ||
| Maximum intensity:255.0 | ||
| Process as 3D?:No | ||
| Relative pixel spacing in X:1.0 | ||
| Relative pixel spacing in Y:1.0 | ||
| Relative pixel spacing in Z:1.0 | ||
| Select the rule criteria:and (file does endwith "_ilastik.tiff") | ||
| Name to assign these images:Ilastik | ||
| Name to assign these objects:Cell | ||
| Select the image type:Color image | ||
| Set intensity range from:Image bit-depth | ||
| Maximum intensity:255.0 | ||
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| Groups:[module_num:4|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['No groups.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] | ||
| Do you want to group your images?:No | ||
| grouping metadata count:1 | ||
| Metadata category:None | ||
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| SmoothMultichannel:[module_num:5|svn_version:'Unknown'|variable_revision_number:6|show_window:False|notes:['This filter will remove strong, single outlier pixels from the images, which sometimes occur in IMC images.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] | ||
| Select the input image:Ilastik | ||
| Name the output image:IlastikFil | ||
| Select smoothing method:Remove single hot pixels | ||
| Calculate artifact diameter automatically?:Yes | ||
| Typical artifact diameter:16.0 | ||
| Edge intensity difference:0.1 | ||
| Clip intensities to 0 and 1?:Yes | ||
| Neighborhood filter size:3 | ||
| Hot pixel threshold:50.0 | ||
| Scale hot pixel threshold to image scale?:Yes | ||
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| SummarizeStack:[module_num:6|svn_version:'Unknown'|variable_revision_number:1|show_window:False|notes:["This calculates an 'average' of all channels and multiplies it with 100.", 'Thus an average count of 0.1 (over all channels) will correspond to 10 in an uint16 image.', '', 'This allows to easily discriminate forground and background.', '']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] | ||
| Select the input image:IlastikFil | ||
| Conversion method:Python Function | ||
| Name the output image:ScaledMean | ||
| Input a Python function:lambda x, axis: np.mean(x, axis=axis)*100 | ||
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| StackImages:[module_num:7|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['Add the summary channel as first channel.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] | ||
| Name the output image:IlastikExp | ||
| Hidden:2 | ||
| Image name:ScaledMean | ||
| Image name:IlastikFil | ||
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| Resize:[module_num:8|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['Scaling up the images 2x makes pixel classificaiton easier.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] | ||
| Select the input image:IlastikExp | ||
| Name the output image:Ilastik2x | ||
| Resizing method:Resize by a fraction or multiple of the original size | ||
| Resizing factor:2 | ||
| Width of the final image:100 | ||
| Height of the final image:100 | ||
| Interpolation method:Bilinear | ||
| Method to specify the dimensions:Manual | ||
| Select the image with the desired dimensions:None | ||
| Additional image count:0 | ||
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| CropImage:[module_num:9|svn_version:'Unknown'|variable_revision_number:4|show_window:False|notes:['This function crops random sections from the images, that are used for training.', '', 'The filename is used as a random seed.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] | ||
| Select the input image:Ilastik2x | ||
| Name the output image:Ilastikcropped | ||
| W width:500 | ||
| H height:500 | ||
| Crop random or specified section?:Crop random section based on metadata. | ||
| X of upper left corner:0 | ||
| Y of upper left corner:0 | ||
| Optional Random Seed:\g<filename> | ||
| Additional image count:0 | ||
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| SaveImages:[module_num:10|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] | ||
| Select the type of image to save:Image | ||
| Select the image to save:Ilastik2x | ||
| Select method for constructing file names:From image filename | ||
| Select image name for file prefix:Ilastik | ||
| Enter single file name:OrigBlue | ||
| Number of digits:4 | ||
| Append a suffix to the image file name?:Yes | ||
| Text to append to the image name:_s2 | ||
| Saved file format:h5 | ||
| Output file location:Same folder as image|scaled | ||
| Image bit depth:16-bit integer | ||
| Overwrite existing files without warning?:Yes | ||
| When to save:Every cycle | ||
| Record the file and path information to the saved image?:No | ||
| Create subfolders in the output folder?:No | ||
| Base image folder:Elsewhere...| | ||
| How to save the series:T (Time) | ||
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| SaveImages:[module_num:11|svn_version:'Unknown'|variable_revision_number:15|show_window:False|notes:['Saves the crop together with the coordinates.', 'This is important to track back were the random crops were exactly taken.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] | ||
| Select the type of image to save:Image | ||
| Select the image to save:Ilastikcropped | ||
| Select method for constructing file names:From image filename | ||
| Select image name for file prefix:Ilastik | ||
| Enter single file name:OrigBlue | ||
| Number of digits:4 | ||
| Append a suffix to the image file name?:Yes | ||
| Text to append to the image name:_x\g<Crop_Ilastikcropped_x>_y\g<Crop_Ilastikcropped_y>_w\g<Crop_Ilastikcropped_w>_h\g<Crop_Ilastikcropped_h> | ||
| Saved file format:h5 | ||
| Output file location:Default Output Folder|crops | ||
| Image bit depth:16-bit integer | ||
| Overwrite existing files without warning?:Yes | ||
| When to save:Every cycle | ||
| Record the file and path information to the saved image?:Yes | ||
| Create subfolders in the output folder?:No | ||
| Base image folder:Elsewhere...| | ||
| How to save the series:T (Time) | ||
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| CreateBatchFiles:[module_num:12|svn_version:'Unknown'|variable_revision_number:8|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:False|wants_pause:False] | ||
| Store batch files in default output folder?:Yes | ||
| Output folder path:/mnt/f2160748-a937-44bd-aca8-3adb8a839612/Data/Analysis/cp4_segmentation_example/cpout | ||
| Are the cluster computers running Windows?:No | ||
| Hidden- in batch mode:No | ||
| Hidden- in distributed mode:No | ||
| Hidden- default input folder at time of save:/home/vitoz | ||
| Hidden- revision number:0 | ||
| Hidden- from old matlab:No | ||
| Local root path:/home/vitoz | ||
| Cluster root path:/home/vitoz |
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