Ilya Belevich
Ilya Belevich
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  • 102 763
Deep learning segmentation projects of FIB-SEM dataset of a U2-OS cell
Video explains how to train and use the trained convolutional neural networks for segmentation of mitochondria, nuclear envelope, Golgi, and endoplasmic reticulum from volume electron microscopy dataset.
Link to the datasets and trained networks:
doi.org/10.5281/zenodo.10043461
Link to the full dataset at EMPIAR:
doi.org/10.6019/EMPIAR-11746
Link to Microscopy Image Browser:
mib.helsinki.fi/
00:00 Introduction
01:18 Zenodo document description
01:48 0_Segmentation: Ground-truth models
02:50 Protocols for generating training sets
05:01 Detection of ER using 2.5D CNN
09:03 Detection of Golgi using 2.5D CNN
14:38 Detection of Mitochondria using 2.5D CNN
15:36 Detection of Nuclear Envelope using 2D CNN
16:51 Concluding remarks
Переглядів: 149

Відео

Segment-anything model with Microscopy Image Browser
Переглядів 6437 місяців тому
Demonstration on how to install and use segment-anything model from Meta AI (segment-anything.com) with Microscopy Image Browser (mib.helsinki.fi) At the current stage there are 7 trained implementations available: vit_h, vit_l, vit_b - default models coming from the original Meta-AI research (*) vit_h_em, vit_b_em - fine-tuned models for electron microscopy ( ) vit_h_lm, vit_b_lm - fine-tuned ...
Deep-learning segmentation using 2.5D Depth-to-Colors workflow in MIB
Переглядів 2767 місяців тому
A new tutorial introducing 2.5D Depth-to-Colors workflow for semantic image segmentation and giving a general update on the best way to do image segmentation using DeepMIB. Link to the datasets and trained networks: doi.org/10.5281/zenodo.10043461 Link to the full dataset at EMPIAR: doi.org/10.6019/EMPIAR-11746 Link to Microscopy Image Browser: mib.helsinki.fi 00:00 Introduction 01:32 What is 2...
MIB Brief: updated 3D volume and surface viewer
Переглядів 287Рік тому
This video demonstrates an updated 3D visualization engine of MIB. At the moment, it works only in MIB for MATLAB. Available in Microscopy Image Browser in version 2.84 See more: mib.helsinki.fi For list of features check: mib.helsinki.fi/features_all.html
MIB Brief: automatic feature-based out of core alignment of datasets
Переглядів 106Рік тому
This quick video demonstrates automatic alignment of images using detected features without pre-loading of the entire image stack. Available in Microscopy Image Browser in version 2.84 See more: mib.helsinki.fi For list of features check: mib.helsinki.fi/features_all.html
MIB Brief: how to link the views between image axes
Переглядів 47Рік тому
This quick video demonstrates how to link the views between loaded datasets. Available in Microscopy Image Browser in version 2.84 See more: mib.helsinki.fi For list of features check: mib.helsinki.fi/features_all.html
MIB Brief: white balance correction
Переглядів 119Рік тому
This quick video demonstrates how to correct white balance in images. Available in Microscopy Image Browser in version 2.84 See more: mib.helsinki.fi For list of features check: mib.helsinki.fi/features_all.html
MIB Brief: Generation of patches for deep learning segmentation
Переглядів 2402 роки тому
This video demonstrates ways to extract image patches from a microscopy dataset for deep learning segmentation. Available in Microscopy Image Browser in version 2.83 See more: mib.helsinki.fi For list of features check: mib.helsinki.fi/features_all.html 00:00 use the annotation tool to select patches for the first class 01:22 use the annotation tool to select patches for the second class 01:52 ...
MIB Brief: Create an image pyramid in TIF file
Переглядів 1992 роки тому
This quick video demonstrates how to convert an image into a TIF image that has a pyramid with different magnifications embedded. Available in Microscopy Image Browser in version 2.83 See more: mib.helsinki.fi For list of features check: mib.helsinki.fi/features_all.html
MIB: Tutorial on 2D patch-wise segmentation using deep learning
Переглядів 7622 роки тому
This example, demonstrates a deep learning workflow for image segmentation in patches. Below is the list of chapters with description. Available in Microscopy Image Browser in version 2.83 See more: mib.helsinki.fi For list of features check: mib.helsinki.fi/features_all.html 00:00 Introduction 02:10 Preview of the expected results 03:06 Extracting image patches 07:30 Resave the dataset as a se...
MIB Brief: Kymograph
Переглядів 1712 роки тому
This video demonstrates generation of kymographs in Microscopy Image Browser. Available in Microscopy Image Browser in version 2.82 Additional information about kymographs: www.sciencedirect.com/topics/medicine-and-dentistry/kymograph Dataset source: Ganguly et al., A dynamic formin-dependent deep F-actin network in axons, J Cell Biol . 2015 Aug 3;210(3):401-17. doi: 10.1083/jcb.201506110. Epub...
210619 Utah is learning to fly
Переглядів 443 роки тому
Если сильно оторваться, то наверное можно взлететь
DeepMIB: features and updates in MIB 2.80
Переглядів 7793 роки тому
Introduction of new features for deep learning segmentation using neural convolutional networks coming with Microscopy Image Browser version 2.80 Tutorials: How to train 2D U-Net for microscopy images: ua-cam.com/video/gk1GK_hWuGE/v-deo.html How to train 3D U-Net for microscopy images: ua-cam.com/video/U5nhbRODvqU/v-deo.html See more: mib.helsinki.fi For list of features check: mib.helsinki.fi/...
MIB Brief: Directory and file operations in batch processing mode
Переглядів 1193 роки тому
Demonstration of directory (create, change, delete) and file (copy, move, delete) operations in the batch processing mode of Microscopy Image Browser Available in Microscopy Image Browser in version 2.80 See more: mib.helsinki.fi For list of features check: mib.helsinki.fi/features_all.html
MIB Brief: Correction of color shifts between color channels
Переглядів 493 роки тому
The video demonstrates how the shifts between color channels may be corrected in Microscopy Image Browser Available in Microscopy Image Browser in version 2.80 See more: mib.helsinki.fi For list of features check: mib.helsinki.fi/features_all.html
MIB Brief: Bulk conversion of images between formats
Переглядів 723 роки тому
MIB Brief: Bulk conversion of images between formats
MIB Brief: Align of datasets using HDD mode
Переглядів 1313 роки тому
MIB Brief: Align of datasets using HDD mode
MCcalc part5: Processing with MCcalc
Переглядів 1303 роки тому
MCcalc part5: Processing with MCcalc
MCcalc part4: Restoration of shuffled models
Переглядів 823 роки тому
MCcalc part4: Restoration of shuffled models
MCcalc part3: Image segmentation
Переглядів 1633 роки тому
MCcalc part3: Image segmentation
MCcalc part2: Rename and Shuffle
Переглядів 813 роки тому
MCcalc part2: Rename and Shuffle
MCcalc part1: Basic image processing
Переглядів 1753 роки тому
MCcalc part1: Basic image processing
MIB Brief: Brush tool
Переглядів 1673 роки тому
MIB Brief: Brush tool
Atlantic puffins
Переглядів 524 роки тому
Atlantic puffins
DeepMIB: How to train 3D U-Net for microscopy images
Переглядів 3,2 тис.4 роки тому
DeepMIB: How to train 3D U-Net for microscopy images
DeepMIB: How to train 2D U-Net for microscopy images
Переглядів 3,1 тис.4 роки тому
DeepMIB: How to train 2D U-Net for microscopy images
SurfaceArea3D: a plugin for analysis of 3D surfaces
Переглядів 3374 роки тому
SurfaceArea3D: a plugin for analysis of 3D surfaces
MIB Brief: Depth to Color Transformation
Переглядів 994 роки тому
MIB Brief: Depth to Color Transformation
MIB Brief: Alignment to Median Smoothed Template (AMST)
Переглядів 1194 роки тому
MIB Brief: Alignment to Median Smoothed Template (AMST)
MIB Brief: Updated Image Filters
Переглядів 1114 роки тому
MIB Brief: Updated Image Filters

КОМЕНТАРІ

  • @chinmayganguly457
    @chinmayganguly457 Місяць тому

    i dont understand what you did in the end with the external directories. i just installed MIB and the GUI looked different when i clicked on external directories. it showed blanks for each of those installation directories. do i have to do anything? plz help

    • @ajaxel
      @ajaxel Місяць тому

      @@chinmayganguly457 Hi, could you post details to forum.image.sc/

    • @chinmayganguly457
      @chinmayganguly457 Місяць тому

      @@ajaxel done, just posted. I just found out about this software. I'm trying to understand how to use U-Net for deconvolution of 3D microscopy images. is it possible?

    • @ajaxel
      @ajaxel Місяць тому

      @@chinmayganguly457 no, you can only do semantic segmentation. As I understand, deconvolution is done by applying PSF to datasets

    • @chinmayganguly457
      @chinmayganguly457 Місяць тому

      @@ajaxel yes. But I already have deconvolved images. Can't I train U-Net to estimate the PSF from that and perform blind deconvolution?

    • @ajaxel
      @ajaxel Місяць тому

      @@chinmayganguly457 @chinmayganguly457 I would not call that deconvolution. It is rather denoising. You need to check something like CARE or noise2void for that. I unfortunately did not have time to implement that in MIB

  • @shinn-tyanwu4155
    @shinn-tyanwu4155 3 місяці тому

    Thanks 😊😊

  • @acitcratna
    @acitcratna 5 місяців тому

    This is truly awesome! are there any plans to allow SAM image embeddings to be calculated from XZ or YZ orthoviews? because that would seriously take this to the next level!

    • @ajaxel
      @ajaxel 5 місяців тому

      good point, I've never tested that. I will add it to the next update, meanwhile if you are on Matlab version, you easily enable that by modifying "MIB/Classes/@mibController/mibGUI_WindowButtonDownFcn.m", where in line 323 change the last parameter from 0 to 1 as: "[w, h, z, t] = obj.mibModel.convertMouseToDataCoordinates(xy(1,1), xy(1,2), 'shown', 1);"

  • @wise1330
    @wise1330 6 місяців тому

    I follow your instruction and upload an EM image to SAM for it to do segmentation for me. I do not see any response, What to do next?

    • @ajaxel
      @ajaxel 6 місяців тому

      Hi, do you have GPU? Send me a message with description and we can check. Also, we have personal zoom meetings available, you can check calendar on mib.helsinki.fi/

  • @mengda9161
    @mengda9161 7 місяців тому

    MIB installation path: F:\Program\MIB2_Matlab MIB: adding "F:\Program\MIB2_Matlab\jars\mij.jar" to Matlab java path MIB: adding "F:\Program\MIB2_Matlab\jars\BioFormats\bioformats_package.jar" to Matlab java path MIB: adding "F:\Program\MIB2_Matlab\jars\MLDropTarget" to Matlab java path Warning: Cannot load an object of class 'TableSelectionStorage': Its class cannot be found. > In matlab.graphics.internal.figfile.FigFile/read (line 31) In matlab.graphics.internal.figfile.FigFile In hgload (line 50) In matlab.hg.internal.openfigLegacy (line 57) In gui_mainfcn>local_openfig (line 286) In gui_mainfcn (line 158) In mibGUI (line 56) In mibView (line 115) In mibController (line 614) In mib (line 123) In run (line 96) Warning: figure JavaFrame property will be obsoleted in a future release. For more information see the JavaFrame resource on the MathWorks web site. > In mibAddIcons (line 49) In mibGUI>mibGUI_OpeningFcn (line 487) In gui_mainfcn (line 220) In mibGUI (line 56) In mibView (line 115) In mibController (line 614) In mib (line 123) In run (line 96)

  • @mengda9161
    @mengda9161 7 місяців тому

    Is Segment-anything model (SAM) is also usable in compiled version?

    • @ajaxel
      @ajaxel 7 місяців тому

      yes, it should work there as well

  • @mengda9161
    @mengda9161 7 місяців тому

    The GUI looks ok except that" Pixel Info " area I can only see the bottom half, cannot see the full text. After I set GUI scale to <1 or >1, it still cannot see. If >1, matlab also crashed,

    • @ajaxel
      @ajaxel 7 місяців тому

      thanks, if you can put a message on forum.image.sc with *mib* tag, I can check that

  • @mengda9161
    @mengda9161 7 місяців тому

    Hi, I am installing MATLAB version in R2016a,it opened the main GUI with no error, but a warning message appered: MIB installation path: F:\Program\MIB2_Matlab MIB: adding "F:\Program\MIB2_Matlab\jars\mij.jar" to Matlab java path MIB: adding "F:\Program\MIB2_Matlab\jars\BioFormats\bioformats_package.jar" to Matlab java path MIB: adding "F:\Program\MIB2_Matlab\jars\MLDropTarget" to Matlab java path Warning: Cannot load an object of class 'TableSelectionStorage': Its class cannot be found. > In matlab.graphics.internal.figfile.FigFile/read (line 31) In matlab.graphics.internal.figfile.FigFile In hgload (line 50) In matlab.hg.internal.openfigLegacy (line 57) In gui_mainfcn>local_openfig (line 286) In gui_mainfcn (line 158) In mibGUI (line 56) In mibView (line 115) In mibController (line 614) In mib (line 123) In run (line 96) Warning: Cannot load an object of class 'TableSelectionStorage': Its class cannot be found. > In matlab.graphics.internal.figfile.FigFile/read (line 31) In matlab.graphics.internal.figfile.FigFile In hgload (line 50) In matlab.hg.internal.openfigLegacy (line 57) In gui_mainfcn>local_openfig (line 286) In gui_mainfcn (line 158) In mibGUI (line 56) In mibView (line 115) In mibController (line 614) In mib (line 123) In run (line 96) Warning: figure JavaFrame property will be obsoleted in a future release. For more information see the JavaFrame resource on the MathWorks web site. > In mibAddIcons (line 49) In mibGUI>mibGUI_OpeningFcn (line 487) In gui_mainfcn (line 220) In mibGUI (line 56) In mibView (line 115) In mibController (line 614) In mib (line 123) In run (line 96)

  • @mengda9161
    @mengda9161 7 місяців тому

    This program evolve to such an unbelivealbe progress

    • @ajaxel
      @ajaxel 7 місяців тому

      Glad you liked it! :)

  • @diwu5012
    @diwu5012 11 місяців тому

    Very useful tutorial! Thank you.

  • @parthjoshi7082
    @parthjoshi7082 Рік тому

    bruh....

  • @jenniferann6956
    @jenniferann6956 Рік тому

    They are so beautiful! 😍🥰🐿️❤️🌸

  • @alexshevelkin3711
    @alexshevelkin3711 2 роки тому

    Great tutorial! Thank you, Ilya. Is it possible to use cDNN to train for segmentation of brain tissue to study morphology of neurons?

    • @ajaxel
      @ajaxel 2 роки тому

      Thank you, Alex! it is definitely possible, but in this case it may be better to start with some simpler segmentations as membranes. I guess the typical workflow for neuroscience is to assemble several networks starting from segmentation of membranes and continue after that to segment cells and their organelles

  • @HenrikSahlinPettersen
    @HenrikSahlinPettersen 2 роки тому

    Excellent tutorial, Ilya! For a tutorial on how to use DeepMIB seamlessly with QuPath (for annotation of whole slide images) and FastPathology (for direct prediction on whole slide images), Ilya and I (and co-workers) have published and arXiv preprint of this and published a tutorial video here: ua-cam.com/video/9dTfUwnL6zY/v-deo.html

  • @HenrikSahlinPettersen
    @HenrikSahlinPettersen 2 роки тому

    Excellent tutorial, Ilya! For a tutorial on how to use DeepMIB seamlessly with QuPath (for annotation of whole slide images) and FastPathology (for direct prediction on whole slide images), Ilya and I (and co-workers) have published and arXiv preprint of this and published a tutorial video here: ua-cam.com/video/9dTfUwnL6zY/v-deo.html

  • @venkteshchalwadi7931
    @venkteshchalwadi7931 3 роки тому

    🔗

  • @aslanturkhan1825
    @aslanturkhan1825 3 роки тому

    Where are the Dataset ? please. you are good teacher

    • @ajaxel
      @ajaxel 3 роки тому

      all details for datasets are in the supporting information at journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008374 direct link: journals.plos.org/ploscompbiol/article/file?type=supplementary&id=info:doi/10.1371/journal.pcbi.1008374.s002

    • @aslanturkhan1825
      @aslanturkhan1825 3 роки тому

      @@ajaxel Hi Ilya. I trained the images I obtained from the normal microscope with U-net and Segnet. I used 15 images for the tutorial. I could not get results after training in U-net. but I got a segmented result. Why didn't U-net produce results? I can send images and training results to your e-mail address.

    • @aslanturkhan1825
      @aslanturkhan1825 3 роки тому

      I got a SegNet result

    • @ajaxel
      @ajaxel 3 роки тому

      @@aslanturkhan1825 sure, I am at work this week, so we can chat about it if you want

  • @tjta9453
    @tjta9453 3 роки тому

    What a beauty

  • @Acuraintegraman1
    @Acuraintegraman1 3 роки тому

    can we download cell models somewhere?

    • @ajaxel
      @ajaxel 3 роки тому

      we have not put this model anywhere. I need to check, probably we can do that

    • @Acuraintegraman1
      @Acuraintegraman1 3 роки тому

      @@ajaxel where can i find cell models online to look at, doesnt have to be yours just good models?

    • @ajaxel
      @ajaxel 3 роки тому

      @@Acuraintegraman1 One of small tutorial datasets is available from mib.helsinki.fi/tutorials_segmentation.html with the upper HTML link. For mitochondria in 3D you can check this: www.epfl.ch/labs/cvlab/data/data-em. If you want something on large scale you can check this one: www.nature.com/articles/s42003-021-01699-w#data-availability In general, it is possible to find those in many places across the net

    • @Acuraintegraman1
      @Acuraintegraman1 3 роки тому

      Ilya Belevich thank you 🙏 this is truly amazing technology!

  • @BiswajitJena_chandu
    @BiswajitJena_chandu 3 роки тому

    plz. provide the link of software

    • @ajaxel
      @ajaxel 3 роки тому

      good point, thank you Download link: http:\\mib.helsinki.fi\downloads.html

  • @laurashankman136
    @laurashankman136 4 роки тому

    This is a really amazing walk through of this application. Can you please make one that is a walk through on how to prepare images? In this you use a test set, but I need to know how to create a good truth dataset for this program.

    • @ajaxel
      @ajaxel 3 роки тому

      ohh, very sorry, I missed the comment... preparation of ground truth datasets may be done in multiple ways depending on your particular data. It is possible to do that with MIB, for example, you can check tutorials from here: mib.helsinki.fi/tutorials_segmentation.html, for our data graphcut segmentation gives most bang for the buck. The other good suggestion to use machine-learning approaches, for example, image classifiers. You can check www.ilastik.org/ for a user-friendly approach.

  • @ОлегЮту
    @ОлегЮту 4 роки тому

    Какой красавец! Поздравляю с хорошим кадром! :)

  • @baoucherafik6317
    @baoucherafik6317 5 років тому

    Good

  • @mengda9161
    @mengda9161 6 років тому

    Below is a reply from Imaris:Settings for File Writers (such as OmeTiff, but also Movie file [slice animation]) that are present in the File Save dialog are not available in the XT interface. The only parameter to be set is the file format (e.g. 'writer="OmeTiff"'), as it is described in the XT interface documentation.>public abstract void FileSave(String paramString1, String paramString2, Map paramMap)Where did you find this method? It cannot be used to specify settings for the Imaris File writing, I assume it is an internal method from the ice library on top of which ImarisXT is built.

  • @mengda9161
    @mengda9161 6 років тому

    I use this command but found that it must has an old dataset to be replaced, but cannot be created de novo into void Imaris window. How do you solve the problem?Thanks.

  • @mengda9161
    @mengda9161 6 років тому

    How do you transfer new matrix to Imaris new window?ImarisApp.GetDataSet.Create?

    • @ajaxel
      @ajaxel 6 років тому

      Hi, I use createDataset function from IceImarisConnector, which creates a dataset with this command: iDataset = this.mImarisApplication.GetFactory().CreateDataSet(); iDataset.Create(classDataSet, sizeX, sizeY, sizeZ, sizeC, sizeT);

    • @mengda9161
      @mengda9161 6 років тому

      Thanks. I got it. This is the correct way to de novo create dataset. By the way, may I ask another two questions about Imaris, Thanks. It is very lucky for me to have Imaris coding expert to discuss with. (1)vApplication = vImarisApplication.GetFactory.CreateApplication; This command create a vApplication, but it seems that it is directed towards the current vImarisApplicatio instance itself. In your opinion what's the potential utility of this command? (2) vImarisApplication.FileSave('D:\QMDownload\a b\Exp.tif','writer="OmeTiff"');. This command is to save the current file as OmeTiff. There are flexible XYZCT configuration and strip/tile setting in format settings of Imaris when clicking SaveAs. I noticed that this code always follow the most recent settings. So I have to change the setting manually. However, what I really need is to use this command to save as OmeTiff with flexible settings automatically in code. Do you know if there is another way/varargin to specify these settings? I tried to search the ImarisLib.jar and found a hidden API as below. It seems that there is a Map object as third argument inside this jar file. As I'm not familiar with java, based on these information, do you think a equivalent Map object could be sent from Matlab to java as the third argument? Or is there other ways to specify it? Thanks. =========== public abstract void FileSave(String paramString1, String paramString2) throws Error; public abstract void FileSave(String paramString1, String paramString2, Map<String, String> paramMap) throws Error; public abstract AsyncResult begin_FileSave(String paramString1, String paramString2); public abstract AsyncResult begin_FileSave(String paramString1, String paramString2, Map<String, String> paramMap); public abstract AsyncResult begin_FileSave(String paramString1, String paramString2, Callback paramCallback); public abstract AsyncResult begin_FileSave(String paramString1, String paramString2, Map<String, String> paramMap, Callback paramCallback); public abstract AsyncResult begin_FileSave(String paramString1, String paramString2, Callback_IApplication_FileSave paramCallback_IApplication_FileSave); public abstract AsyncResult begin_FileSave(String paramString1, String paramString2, Map<String, String> paramMap, Callback_IApplication_FileSave paramCallback_IApplication_FileSave); public abstract void end_FileSave(AsyncResult paramAsyncResult) throws Error;

    • @mengda9161
      @mengda9161 6 років тому

      public void FileSave(String paramString1, String paramString2) throws Error { FileSave(paramString1, paramString2, null, false); } public void FileSave(String paramString1, String paramString2, Map<String, String> paramMap) throws Error { FileSave(paramString1, paramString2, paramMap, true); } The FileSave(String paramString1, String paramString2) was reloaded to FileSave(paramString1, paramString2, null, false), while FileSave(String paramString1, String paramString2, Map<String, String> paramMap) was reloaded to FileSave(paramString1, paramString2, paramMap, true). There should be a third argument. I cannot find detailed document about the third argument, and do not know how to send Map<String, String> paramMap to java. I do not know the supposed content of Map itself. Could you help me, Thanks.

    • @mengda9161
      @mengda9161 6 років тому

      I'm not sure if java.util.HashMap would work.

    • @mengda9161
      @mengda9161 6 років тому

      The following code worked!!!!!!!!! a = java.util.HashMap(); a.put('wefew','wfewe'); vImarisApplication.FileSave('D:\QMDownload\a b\Exp.tif','writer="OmeTiff"',a); This command does not throw error, means that there is a way to indicate 3rd argument! Wow! I got a breakthrough now! Then next problem is the content of the Map.

  • @mengda9161
    @mengda9161 6 років тому

    Hi

  • @felipelopesmachado9295
    @felipelopesmachado9295 6 років тому

    Beutifullllllll from Brazilllllllll 👍🏾👍🏾👍🏾👍🏾👍🏾👍🏾👍🏾👍🏾👍🏾👍🏾👍🏾👍🏾👍🏾👍🏾👍🏾👍🏾

  • @ajaxel
    @ajaxel 11 років тому

    A short video of Brown Pelicans from La Jolla, California