![]() ![]() Sage D, Neumann FR, Hediger F et al (2005) Automatic tracking of individual fluorescence particles: application to the study of chromosome dynamics. Kamentsky L, Jones TR, Fraser A et al (2011) Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software. \Ĭarpenter AE, Jones TR, Lamprecht MR et al (2006) CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Now, note that there is a module, EnhanceOrSuppressFeatures, that is specifically capable of transforming DIC images into something that is readily segmented. While these fragments could be useful for simple cell counting, most metrics of morphology will be inaccurate. Īnwar T, Liu X, Suntio T et al (2019) ER-targeted Beclin 1 supports autophagosome biogenesis in the absence of ULK1 and ULK2 kinases. Thresholding renders the CHO cells into moon-like crescents. Klionsky DJ, Abdel-Aziz AK, Abdelfatah S et al (2021) Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)(1). To fully emulate the behaviour of the standalone CellProfiler in Galaxy, each image analysis workflow needs to have three parts: 1) StartingModules to initialise the pipeline, 2) tools performing the analysis ( Fig. Any suggestion would be appreciated.Ģ017_11_29_RecognizedCode-12-2_4_AF488.Kabeya Y, Mizushima N, Ueno T et al (2000) LC3, a mammalian homologue of yeast Apg8p, is localized in autophagosome membranes after processing. Image granularity is a texture measurement that tries to fit a series of structure elements of increasing size into the texture of the image and outputs a spectrum of measures based on how well they fit. Also, in my current run, it takes a long time to run each cycle, is there any other way to make it faster?Īttached are two of the images I’m analyzing. MeasureGranularity outputs spectra of size measurements of the textures in the image.If there’s no other possible way to resolve it, then I probably could live with it. I changed the Java memory to 2200 and number of worker to 2 and let it sit without doing anything else on the computer. Could this thresholding method in my pipeline seem be an issue though?Īnd I tried the combination of your suggestions, but still have this issue, on the 4th cycle. ![]() Yes I have changed my thresholding strategy to Otsu’s method, very sorry for the confusion. Is there anything in my pipeline seem to be problem-causing?įile “cellprofiler\pipeline.pyc”, line 1956, in run_image_setįile “cellprofiler\pipeline.pyc”, line 2067, in run_moduleįile “cellprofiler\modules\applythreshold.pyc”, line 139, in runįile “cellprofiler\modules\identify.pyc”, line 864, in threshold_imageįile “cellprofiler\modules\identify.pyc”, line 1010, in get_thresholdįile “centrosome\threshold.pyc”, line 110, in get_thresholdįile “centrosome\threshold.pyc”, line 174, in get_global_thresholdįile “centrosome\threshold.pyc”, line 286, in get_otsu_thresholdįile “centrosome\otsu.pyc”, line 31, in otsuįile “centrosome\otsu.pyc”, line 252, in running_varianceįile “numpy\core\shape_base.pyc”, line 275, in hstack However, I still have this MemoryError, at the ApplyThreshold step starting from the second cycle.īy the way, my files each is 40MB, if I have total of 48 of them, would that cause any problem?Īnd would the temporary files generated at each module take up memory too?įor the Installed RAM, I have 16 GB usable Project_IHC_cell_counting_PV_488_3.cpproj (455.1 KB)Įxception in CellProfiler core processingįile “matplotlib\backends\backend_wx.pyc”, line 955, in _onPaintįile “matplotlib\backends\backend_wxagg.pyc”, line 51, in drawįile “matplotlib\backends\backend_agg.pyc”, line 474, in drawįile “matplotlib\artist.pyc”, line 61, in draw_wrapperįile “matplotlib\figure.pyc”, line 1133, in drawįile “matplotlib\axes_base.pyc”, line 2304, in drawįile “cellprofiler\gui\cpfigure.pyc”, line 1984, in drawįile “cellprofiler\gui\cpfigure.pyc”, line 1450, in normalize_imageįile “matplotlib\cm.pyc”, line 262, in to_rgbaįile “matplotlib\colors.pyc”, line 612, in callĬlosing the windows definitely helped it to get through the first cycle. What could my problem? Attached my pipeline here. I set the maximum space allowed for java (File>Preferences) to 1500 MB, otherwise I would running into the problem of Java heap space error (unless I can fix it another way?) I’m running into the problem of memory error while analyzing my images (at ApplyThreshold step) and not even one single image can run through the pipeline because the program stops before finishing it. I am using a CellProfiler version 2.2 on my Windows 10 圆4-based operating processor.
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