![]() ![]() For the lipid droplet analysis, we used two approaches, the free online computer software of reference, ImageJ, and another free online computer software, CellProfiler. Therefore, the aims of this study were to develop an accurate, standardized approach to quantify lipid droplet size of mature adipocytes and a clustering approach to analyze the total lipid content per adipocyte. Nutrition, stress, or chemical exposure can dysregulate adipogenic differentiation and lipid metabolism. However, imaging tools for evaluating intracellular lipid droplets remain at their infancy. During differentiation, neutral lipids that accumulate in adipocytes can be detected using stains and used as an index of cell differentiation. Looking forward to hearing from you.Adipogenic differentiation is the process by which preadipocytes become mature adipocytes, cells that store energy and regulate metabolic homeostasis. I figured its an alternative way to find more accurately the dust particles. I could put this image through the ApplyThresholdModule, convert to binary and save as an image. Kindly find my pipeline,project, test image and created mask here Īs an aside, I noticed that in the ColorToGray module, if the conversion method is set to combine and a relative weight of zero is assigned to the green channel, the resulting image is essentially the dust particles. I pretty sure I’m doing something wrong but can’t figure out what. I then used the ImageMath to multiply each channel with the mask. I used ColorToGray to split channels into RGB What did you mean by ’ PUT the individual channels through MaskImage to mask out the dust that you wanted excluded’ Hi Beth, me again I have been playing this mask business but it seems to be eluding me. No, the idea is you use ColorToGray to split your channels, put the individual channels through MaskImage to mask out the dust that you wanted excluded, and then IdentifyPrimaryObjects on the masked images to find your objects you were doing timelapse on and do whatever other analysis you like! Do I need to use ImagemMath to invert the mask? After inversion does it still remain a binary image? My dust was white and my background was black (UsedToCreateMask.cppipe and UsedToCreateMask.cpproj). For my mask, I got a black and white image. I put both the project and the pipeline in google drive at the end of the text. Save as a tif, not as a jpg (jpg is almost never a good idea) You want this to be good because you’re going to use this for the rest of your images.-Optional: use IdentifyPrimaryObjects to identify “dust particle objects” within your -SaveImages - if you are coming from ApplyThreshold, save it as an Image (not a Mask, which apparently only comes from Crop- we should probably rename that, our bad) if you’re coming from IdentifyPrimaryObjects save type is Objects. Feel free to play with the threshold a bit in test mode- to my eye it looks like 0.55 may be a little lenient, try maybe 0.53 or 0.52. ![]() ![]() Take one of your input images, use ApplyThreshold for masking. Now identify your nuclei or whatever else using IdentifyPrimaryObjects on the masked image. Repeat on as many channels as needed you can try doing it just once upstream of ColorToGray but I’m not sure how the behavior will propagate. Whether you’re using an image or objects to mask is once again based on what you chose above. Downstream of your ColorToGray, use “MaskImage”. Its type will be either “Binary mask” or “Objects” based on what you chose above. Load all of your images as you normally would, then in NamesAndTypes load your mask image using “Load a single image”. Save as a tif, not as a jpg (jpg is almost never a good idea). SaveImages - if you are coming from ApplyThreshold, save it as an Image (not a Mask, which apparently only comes from Crop- we should probably rename that, our bad) if you’re coming from IdentifyPrimaryObjects save type is Objects. Optional: use IdentifyPrimaryObjects to identify “dust particle objects” within your ![]() You want this to be good because you’re going to use this for the rest of your images. This is what I suggest you do, let me know if it makes sense It looks to me like you’re trying to mask objects named Nuclei by themselves, which would probably explain your AssertionError overall though I don’t understand your workflow right now, and since I only have the cppipe and not the cpproj I can’t be sure exactly what the disconnect is. ![]()
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