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Hello, thanks for reaching out. Try changing the threshold value ranging from 50-150 in the wound healing tool options window and then run the macro again. The threshold value depends on the contrast of the cells and its background. sometimes the image dimensions are in pixels or inches and radius close value needs to be changed accordingly. If still it does not work out, send me a sample image to troubleshoot it.

Hi thanks for reaching out. it did not happen to me so far. Can you send me a sample image? I will try to troubleshoot it.

@@nrttaye4033 Hiiii, thanks for answering me :D I was messing around with Fiji and ended up finding the setting described below: image> adjust> auto crop (guess background color) I put it in macro and it worked, thank goodness. anyway, thanks for the guidance, you always help me. all the best!

You figured it out, Excellent! All the best with your analysis.

yes it works. The ROI manager will pop up after running the macro. Using the ROI manager window you can identify which nuclei are being referred to.

Hi, thanks for reaching out. Here is the link to download ImageJ. choose the version that suits your operating system imagej.net/ij/download.html

have a look at this video from 0:00 to 0:45 seconds, it shows how to install imagej

hello, thanks for reaching out. Does the graft look like hairs with certain length or just transplanted with round shape structures? I may need to know how the transplant images looks like before coming to a conclusion. If they appear like cilia/filament i have video tutorials on how to count these ruclips.net/video/b3Z2t62i9Ds/видео.html if you have overlaps then try "ridge detection" plugin github.com/thorstenwagner/ij-ridgedetection let me know if these helps. Sure happy to help.

@@nrttaye4033 hello again , can I send for you one of my plate with specific number of hair graft ?

Can I have your Email address?(for send a image of graft)

here is my email

@@nrttaye4033 thank you .I sent for you an email

you are welcome. listing intensity of each cells would require a ROI/specific boundary/selection of each cells while thresholding. in this video the selection command uses "select all". However, to do individual selection either the cells do not adhere/touch one another or a manual seperation would be needed. For instance the DAPI is already seperated in this video. during the analyze and measure steps check the "add to manager" option in the ROI manager window to get individual cell intensity. Here is a demo video ruclips.net/video/hpxnbJ_8EE4/видео.html where i analyzed the intensity of each DAPI seperately.

The plot results instructs the Weka core to generate the model performance chart, which includes curves for ROC, precision/recall, and other metrics based on the training dataset. These curves demonstrate the classifier's performance based on the many thresholds that can be applied to the probability maps. A receiver operating characteristic curve, or ROC curve, is a graphical figure that shows the performance of a binary classifier model (which can also be used for multi-class classification) at different threshold values. The ROC curve plots the true positive rate (TPR) vs the false positive rate (FPR) at each threshold setting. The ROC can alternatively be viewed as a plot of statistical power vs Type I Error of the decision rule. The ROC curve represents the sensitivity or recall as a function of the false positive rate. Precision and recall are performance measurements used in pattern recognition, information retrieval, object detection, and classification (machine learning) to assess data recovered from a collection, corpus, or sample space.Precision (also known as positive predictive value) is the proportion of relevant instances among the recovered ones. Recall (also known as sensitivity) is the proportion of relevant instances that were recovered. Relevance thus serves as the foundation for both precision and recall.

The previous video showed how to convert the czi files into individual jpeg images. Using this method is laborious and time-consuming. The macro code in this video is quite useful for batch processing. I hope this macro is saving many users.

Hello, I think you can set scales. Have a look at this publication onlinelibrary.wiley.com/doi/10.1111/srt.12634 let me know if this helps.

Hello Merve, nice to hear from you again. you can set scale in micrometer if needed. The "branch length" is assigned to an skeleton id. the comparison will be the many branch lengths of one image vs many branch length of another image. you may plot the graph as box plot, or dot plots or average bar graph. Because the image may contain some areas that do not belong to a neuron, the results may occasionally include skeleton ids with no branch length (zero) and sometimes a short length. here is an interesting discussion forum forum.image.sc/t/neurite-branch-length-number/95022

@@nrttaye4033 Thank you for the reply. It helped me so much.

hello I agree the link is not working. Here is an alternate link. All the best. imagej.net/ij/macros/toolsets/Angiogenesis%2520Analyzer.txt

You may or may not normalize with DAPI. it totally depends on the specific biological questions being asked. Normalization in such a situation is usually done with cell number count or Dapi fluorescence to match the biological questions being asked. Here is a random article for your reference (Figure 3) www.ncbi.nlm.nih.gov/pmc/articles/PMC6075439/

Hello, i am not yet aware of any macros as of now that can measure the length of slightly round/irregular objects (nucleus shape). the closest to any automatic length measure I know is of filaments (ruclips.net/video/CP2A-Jt279c/видео.html) and objects that are strainght and placed in either X or Y axis (ruclips.net/video/Jr2ehzIzoYQ/видео.html). I will get back to you if I come across any macros to measure the cell length automatically.

@@nrttaye4033 thank you so much

You are very welcome. Glad you are finding it useful. the formula for leaf disease percentage is (diseased leaf area/Total leaf area) X 100.

You are very welcome. Glad you found it useful.

hello i agree the link is not working. Here is an alternate link. All the best. imagej.net/ij/macros/toolsets/Angiogenesis%2520Analyzer.txt

Hello, there are two update options "update ImageJ" and "update". Click on the later one.

@@nrttaye4033 I have figured out the update part but when I tick on FFMPEG it says "3 files are installed from the site FFMPEG and will be updated/uninstalled"

No problem, just go ahead and install these updates

@@nrttaye4033 I did sir, but I am not able to load the AVI file from import. In fact, when I select "Import" I do not get the option "movie "FFMPEG". When I go back to square one by clicking "update", the FFMPEG option remains unchecked and I'll have to tick it again. Where did I go wrong? I had converted an mp4 file to AVI to import it on FIJI software, could that be the problem?

Could you try making a right click (for windows) on "m"?

@@nrttaye4033 oh Lord. Thank you very much. It worked.

Hi, Welcome. I am not sure if this plugins will help in counting the fenestra. Have you tried this way...change to 8 bit, threshold, analyze particles and count the numbers? Let me know if this works.

@@nrttaye4033 Hi, thank you for the response. Yes, I tried but when I set the threshold, the fenestra is not seen and not detectable. That's why analyze particles and count number did not work.

sometimes when the fenestra color matches with the background color such issues can come up. If there is a slight change in color, a) a background corrrection or b) a weka segmentation can be performed (ruclips.net/video/tmPr5Iw_9XY/видео.html) Could you try this out? If it still does not work, send me a sample image and i could try the troubleshooting.

@@nrttaye4033 Hi, thank you so much for the response. Unfortunately, it does not work. If you could give me an e-mail address, I could send you.

here is the email address nandarajtaye@outlook.com

Hello, yes simply leave the cells blank

you are welcome. Glad you found it useful

Hello, here are two random articles for your reference www.ncbi.nlm.nih.gov/pmc/articles/PMC6582399/ (please check figure 1) and www.ncbi.nlm.nih.gov/pmc/articles/PMC6075439/ (please check figure 3). Could you also try uncheck the "dark background" in the threshold window. if this step already provides you B/W image you can ignore the binary step. Let me know if that worked

hello, in the threshold window could you uncheck the "dark background" and try again.

Welcome! You raised a very important question. Measuring intensity without thresholding is performed for those images when "limit to threshold" option is applicable and equal area size of staining is not accounted. On the other hand In those images when the equal area size or region of interest of staining is also to be considered such as in a comparison like ctrl vs treatment, thresholding the image is performed.

Yes, it is a good idea to subtract background if any. However, it may or may not affect much if the "limit to threshold" is selected.

Hello, Thank you for reaching out. Here is a link to another video that may solve your concern ruclips.net/video/cc-bryk_ihw/видео.html

Hello, welcome. Please try adjusting the bottom slider in the threshold window too and adjust the upper slider accordingly. Auto threshold is also another option you could try out. If it still does not solve the issue , please send me a sample image for troubleshooting

​@@nrttaye4033 Thank you so much for the response. I will try it. My other question is how could I perform the analysis? I mean how can I compare this kind of data with other group of z stack images? Thank you.

This way of analysis is same as comparing the MFI of different single images. Using the same number of slices, thresholding data, brightness/contrast and maintaing all other parameters equal for all the z stack images for comparison should be good enough to get the data.

@@nrttaye4033 Thank you so much for the response. For instance, I have 15 slices for one sample and 18 slides for the other one. Then, to compare the number of slices must be equal? Then, should the step size be equal for each sample?

hello, welcome. with regards to your sample size, it alright to compare between two groups of unequal size. The statistics is needed to be considered here. Since, a stundent's t test cannot be performed in this scenerio, you may have to consider a Welch's t test. Have a look at this discussion (www.researchgate.net/post/How-to-compare-two-samples-with-different-sample-size). In addition, you might have to be cautious while doing the brightness and contrast settings as this changes the pixel values. If not required, avoid the brightness and contrast adjustments. In case you want to change it, there are other methods to increase the brightness without changing the pixel values. all the best with your quantification.

Hello, thanks for reaching out. could you please try the plugin from this video? ruclips.net/video/U0W6KOcgnZU/видео.html

welcome. to watershed manually, please visit this video ruclips.net/video/P09_sg4yEug/видео.html let me know if this helps

@@nrttaye4033 Thank you very much. I realize that to achieve a good watersheding, I have to have a nice thresholded pictures. I took some DIC pictures for budding yeast cells. The issue is that the interion of the cells are similar in color to the background, so when I do thresholding, the program regarded the cell interion and background the same thing, but the good thing is that the outline of the cells are clear, which can be singled out to form binary picture with cells' outline. But the issue is that some of the outline is open circled as opposed to being a closed circle. Could you please give me some suggestion to work around this issue?

Hello, sure. This might help you out to some extent ruclips.net/video/Tu9UlDspsZM/видео.html In this video, i am measuring the cross section area, however some circles are incomplete. It can be fixed manually. Have a look between 1:30 to 2:15 minutes in the video. Select the same color of your cell outline and close it using the brush tool. All the best

@@nrttaye4033 Thank you very much! really appreciate your help

Glad you found it useful. Here is an interesting discussion on this topic www.researchgate.net/post/Does-anyone-have-a-protocol-for-quantifying-IHC-images-in-ImageJ

Thanks

may not be specific to cd45. let me know what type of staining is that for eg IF, IHC etc.

@@nrttaye4033 IHC. Thanks :)

@@nrttaye4033 IHC. Thanks :)

You are welcome. Here are videos for IHC staining ruclips.net/video/K1WKcbKUOMY/видео.html ruclips.net/video/NxNEf1XSPTk/видео.html

Hello, here the unit of length is in pixels. You may convert to any unit of your choice for instance to micro meter

Hello, Please see 1) uncheck the dark background while thresholding. 2) in the set measurements option uncheck limit to threshold. Even if this does not help, try inverting the object to black and white background by clicking on edit and select invert. Let me know if this helps

Welcome. Glad you found it useful

Hello. I think this formula can be used to convert pixels to mm. millimeters = (pixels X 25.4) / dpi. You may also find calculators online to calculate it automatically.

hello, thanks for reaching out. Please try updating the bioformats plugin, or remove the old one and install the plugin again. Here is an alternative video to convert zen file to tiff automatically ruclips.net/video/cc-bryk_ihw/видео.html

the zen lite software can be downloaded and installed in windows os system. here is the link www.zeiss.com/microscopy/en/products/software/zeiss-zen-lite.html

Thanks for watching my youtube videos. Outlook or gmail does not allow me to send .jar files as it is considered executable file. However, I just found out that this plugin is not supported by the latest ImageJ software update. Please use the older version of the program and run the plugin again. All the best with your analysis.

You are welcome. Glad you found it useful.

Thank you Nandu. Glad you found it useful.

Please use a different threshold color such as B/W for the red image.

You are welcome. glad you found it useful

hello, here are some interesting discussions on whether to keep the same thresholding values for different images. Researchers seemed to be divided using the threshold maintenance. I also tried to use auto threshold and it was returning me different values for both images. Let me know what you think. forum.image.sc/t/setting-the-same-thresold-for-all-images-for-different-conditions-and-then-analyze-the-particles/20855 www.researchgate.net/post/Setting_threshold_when_analysing_image_data forum.image.sc/t/how-to-threshold-control-for-background-and-format-image-for-fluorescence-intensity-measurement/4607/2 From the materials available I could see that alternative solutions are available to prevent biased analysis either by keeping the threshold constant across all images or changing them according to the image types. These are Adaptive thresholding or Histogram thresholding. However, I have not used these so far.

please see your previous comment for the answer. Thanks for reaching out

@@nrttaye4033 I am also interested in this, would I also be able to get this information? how can I quantify the difference in groups and markers?

Hello please check out this video ruclips.net/video/IQTSsXVOQk0/видео.html let me know if this video answers your query.

Hello, if you want to calculate the area and intensity of only the stained regions, then select the "limit to threshold". it is available under analyze, set measurements, limit to threshold. This method can also be used. selecting limit to threshold is much simpler

the distance to mm can be calculated using the scale bar in the image.

Hello, I am not quite sure about this new issue. once the image is 8 bit, could you change the color and try the analysis again. to change the color go to image, lookup tables, and click on grays. let me know if that worked.

@@nrttaye4033 thank you. I clicked in the image, then type, then 8 bit, and then the image went from coloured to B&W

to calculate the Nuclear/Cytoplasmic ratio, simply divide the staining mean intensity i,e MEAN of nuclear/ mean of cytoplasmic. The Mean value is in the results window.

Unique times on a Kaplan-Meier curve are critical for determining when events occur, recalculating survival probabilities, and appropriately expressing these changes in survival estimates. They ensure that the stepwise nature of the Kaplan-Meier curve appropriately depicts the survival experience of the group under study. Time zero, often known as the time origin, is the point at which individuals are deemed at risk for the result of their interest. Many studies quantify time at risk from the beginning of the trial (i.e., enrollment). So it is considered that the patient is alive at this time and zero is used.

Hello, it looks like the site is down. I can send you the plugin if you provide your email

@@nrttaye4033 Can you send me?

please send me your email at ... i figured the link is not working, i can send you the plugin.