All super helpful. Thanks for the details. I'll try to tackle soon. Best!
Jay > On May 15, 2015, at 7:04 AM, Christian Dietz > <christian.di...@uni-konstanz.de> wrote: > > Hi Jay, > > See my answers below. I hope this helps. > > Christian > > > > On 14.05.2015 20:44, Jay Warrick wrote: >> Hi Christian, >> >> Thanks so much! This helps a lot. I probably wouldn't have discovered the >> tools for labeling immediately without your suggestion. Although I've gone >> through the tutorials, I'm still new to ImgLib2 so I wonder if I could try >> to summarize what I think the general workflow to be with an example and >> maybe you can correct me / direct me as I go? As a place to start, I'm >> imagining a scenario where I have a 1-plane, 1-channel nuclear stained image >> of cells and its associated thresholded image to >> identhttps://github.com/imglib/imglib2-roi/tree/master/src/main/java/net/imglib2/roiify >> nuclear regions for quantifying feature sets. At a high-level, what I >> imagine trying to do is... > > In KNIME we are still using the deprecated versions of the Labeling. Tobias > Pietzsch rewrote parts of this framework (thats why NativeImgLabeling for > example is deprecated). The new implementations, you can find here: > https://github.com/imglib/imglib2-roi/tree/master/src/main/java/net/imglib2/roi > > <https://github.com/imglib/imglib2-roi/tree/master/src/main/java/net/imglib2/roi>. > We are going to switch to these implementations in KNIME soon. > >> >> 1) Generate a labeling object. For example, using the following... >> >> final Labeling< T > labeling = new NativeImgLabeling< T, IntType >( Img < T >> > ); > > In the new ROI implementations you would use ImgLabeling > (https://github.com/imglib/imglib2-roi/blob/master/src/main/java/net/imglib2/roi/labeling/ImgLabeling.java > > <https://github.com/imglib/imglib2-roi/blob/master/src/main/java/net/imglib2/roi/labeling/ImgLabeling.java>) > instead of NativeImgLabeling. > >> >> I assume this simplified constructor takes what could be a "black and white" >> image and associates Long numbers with each separate region of white pixels. >> Right? How might I reassign labels or construct them if, for example, I have >> specific IDs that I would like to associate with each white region of the >> mask image I would like to label? > > Actually, the constructor takes an Img of arbitrary integer-type which serves > as an index image. From each Integer there exists a mapping to a Set of > labels. If you want to derive a Labeling from a "Black and White" image, you > have to apply an algorithm. For example a Connected Component Analysis (this > is one way to do it in KNIME, for example after a simple thresholding), to > identify the individual objects in your "Black and White" image. > >> >> 2) Once I have a labeling, it seems like the next step is to obtain an >> IterableInterval over an ROI that can return "x-y locations" of pixels with >> a particular label. I assume to get this I would use something like... >> >> labeling.getIterableRegionOfInterest(i).getIterableIntervalOverROI(src) > > Right! In the new implementations you would do something like: > > ImgLabeling<String, IntType> labeling = new ImgLabeling<String, IntType>(...); > LabelRegions<String> regions = new LabelRegions<String>(labeling); > Iterator<LabelRegion<String>> labelIter = regions.iterator(); > > and then use Regions.sample(...) to overlay the region on some arbitrary > image. >> >> I can see where sometimes I only care about the shape of the ROI (e.g., with >> Zernike shape features) and other times I want pixel intensities at those >> locations (e.g., texture features). For the latter case, I assume "src" >> could be an image whose pixel values I'm interested at these locations, >> essentially applying an ROI to a particular image. Right? For other >> scenarios where only shape matters, would I use >> "labeling.getRegionOfInterest()" and that would be sufficient? Does the >> Zernike feature set prefer ROIs that define the boundaries of the shape or >> the whole region of the shape and it figures out the boundaries itself? > > Correct. In some cases (e.g. Shape) the input is just the LabelRegion (new > wording from new implementation of Tobias), in other cases you want to sample > over the pixels of another image in this region (Regions.sample()). > >> >> 3) Then I suppose I loop through the labels in the "labeling" object to get >> these ROIs and pass them to the FeatureSet ops accessing the data as you do >> in the provided example and storing the data however I like. >> >> Is that about right? > > Sounds good. > >> >> Lastly, related to Step 1,it looks like a labeling can hold multiple labels >> for each pixel location. Is the idea there to allow regions to overlap? > > Absolutely. Overlap or more meta-information about objects (TrackID, > Classification Result, ...). > >> If I'm generally interested in keeping pixels associated with a maximum of >> one cell, would I use this feature for anything else and if so, what sort of >> workflow is envisioned for creating these different labelings and >> essentially ending up with the merged information in a single labeling >> object? > > Speaking about workflows: On > https://tech.knime.org/community/image-processing > <https://tech.knime.org/community/image-processing> there is an example > workflow called High-Content-Screening where we make use of a labeling. Maybe > this helps you, too. > >> >> Thanks!!! >> >> Jay >> >> >> >> >>> On May 13, 2015, at 8:22 AM, Christian Dietz >>> <christian.di...@uni-konstanz.de <mailto:christian.di...@uni-konstanz.de>> >>> wrote: >>> >>> Hi Jay, >>> >>> you are right, we are working on this project since a while. The goal of >>> the work we are doing is to have efficient implementations for most of the >>> well known features which can be derived from images or ROIs. The main work >>> is done on the following branch: >>> >>> https://github.com/imagej/imagej-ops/tree/outputop-service >>> <https://github.com/imagej/imagej-ops/tree/outputop-service> >>> >>> and there is an open issue documenting the process: >>> >>> https://github.com/imagej/imagej-ops/issues/67 >>> <https://github.com/imagej/imagej-ops/issues/67> >>> >>> A very small example how to use the features is given at: >>> >>> https://github.com/imagej/imagej-ops/blob/outputop-service/src/main/java/net/imagej/ops/features/Example.java >>> >>> <https://github.com/imagej/imagej-ops/blob/outputop-service/src/main/java/net/imagej/ops/features/Example.java> >>> >>> Concerning your question with ROIs: The features implementation do not >>> really care if they get an Img or a ROI. The only thing they expect is to >>> get some IterableInterval or Iterable or RandomAccessibleInterval etc >>> (depends on the type of feature). In KNIME we use Labelings >>> (https://github.com/imglib/imglib2-roi/tree/master/src >>> <https://github.com/imglib/imglib2-roi/tree/master/src>) to describe our >>> segmentations and derive or ROIs. >>> >>> Does this help you? It would be great if you want to contribute to the >>> outputop-service and maybe implement some of the missing features. >>> >>> Best, >>> >>> Christian >>> >>> >>> >>> >>> On 13.05.2015 06:27, Jay Warrick wrote: >>>> Hi All, >>>> >>>> I was hoping to find some info on the 'feature service' or 'haralick' >>>> branch of imagej-ops (at least those look like to two most developed >>>> branches for feature extraction). The creation of feature set ops is a >>>> really great idea and thanks to everyone who is working on it. Likewise, I >>>> would certainly be willing to try and help fill out some features if it >>>> seems appropriate, especially when I get more familiar with the ops >>>> framework. Also, please let me know if there are any concerns with me >>>> using any of these tools prior to the authors publishing on/with these >>>> implementations themselves. My work is still preliminary, but just wanted >>>> to ask to be safe. >>>> >>>> I realize the 'feature service' and 'haralick' branches are somewhat WIPs >>>> but it seems there are many rich feature sets that appear to be nearly or >>>> completely implemented and was hoping to try and use them if possible... >>>> Towards this goal, I was able to use the FirstOrderStatFeatureSet and >>>> ZernikeFeatureSet classes to get information from an Img / ImgPlus / >>>> SCIFIOImgPlus using the example provided in the branch. However, it is >>>> unclear to me how the classes should be used to do this for each cell in >>>> an image. Is it assumed that we are feeding in small cropped and masked >>>> regions to the feature set ops? If so, suggestions on an efficient way to >>>> do so (or links to examples in other projects... Knime?) would be amazing. >>>> I'm generally able to identify cells and create ROIs and mask images etc >>>> programmatically in Java with ImageJ classes, but haven't done so with >>>> Img-related image objects yet. With a hint or two, I can try and take it >>>> from there. Maybe do the cropping etc with old I >>>> mageJ classes and wrap the resultant cropped regions in Img objects? >>>> Maybe I'm way off base and I'm supposed to be using ROIs somewhere in the >>>> mix with the ops. Hopefully someone can set me straight :-) >>>> >>>> Thanks a bunch in advance. >>>> >>>> Best, >>>> >>>> Jay >>>> _______________________________________________ >>>> ImageJ-devel mailing list >>>> ImageJ-devel@imagej.net <mailto:ImageJ-devel@imagej.net> >>>> http://imagej.net/mailman/listinfo/imagej-devel >>>> <http://imagej.net/mailman/listinfo/imagej-devel> >>> >>> >>> >>> _______________________________________________ >>> ImageJ-devel mailing list >>> ImageJ-devel@imagej.net <mailto:ImageJ-devel@imagej.net> >>> http://imagej.net/mailman/listinfo/imagej-devel >>> <http://imagej.net/mailman/listinfo/imagej-devel> >> >
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