I am learning all about image analysis using python with your channel! Your tutorials are amazing! Great work to the scientific community! Thanks a lot!
Wow....that works amazing with my fibrotic tissue images! Just out of the box near perfect results in separating healthy from fibrotic tissue! Keep your tutorials coming! Best wishes from Germany!
Very interesting video always like your way of explaining and simplifying things well done. I am working on a large histopathology brain tumor image svs format is there any way to normalize those large images?. I tried to export tiles from those large images using qupath and tried individual tile on the python code you presented to normalize it it worked but not sure how can I normalize too many tiles images(1000 and above) at once ?.
the new video is just for u. see also: digitalslidearchive.github.io/HistomicsTK/examples/color_normalization_and_augmentation.html never tested personaly, but if u could make it work let me know pls
Hi DigitalScreeni! Thank you for the video. I was just going though the paper and there is one thing I do not understand. Why do you use in your code the refence matrix HERef? An where does it come from? As far as I can tell there is no mention of the reference mixing matrix in the paper. Is it not the point of the paper to automatically determine the stain vectors so that no pre-determined matrices need to be used? I am confused.
Nice video Sreeni. Really benefiting my work! One question: How would it be possible to remove noise particularly these histology slides? Applying Filters? Keep up the good work!
I am not familiar with MATLAB functionality. This video shows the normalization process of H&E stained images and it shouldn't matter what type of sample as long as it is H&E stained.
I have tried this with MITOS ATYPIA14 dataset which are fully H&E stained images but nuclei segmentation using watershed algorithm isn't working properly. What to do?
That is a tough one :) It is easy to find existing libraries and use its functionality. It is very time consuming to write code for big algorithms, usually part of thesis work. Let us hope someone creates a library that we can use.
Thanks. Please don't worry about citing me, I am doing this to educate people. Also, my videos do not have original research content that's worth citing. If you want to thank then you can cite this RUclips channel.
Hello sir. I have 20 different types of English alphabets images. In each type there are total 2000 images of all alphabets. That means set one has all englisgbalphabetsband it contains 2000 images. So the total database is of 40000 images. So should I use different classification model for each set out of 20 or I should use all.40000 images in one model. I want to use machine learning not deep learning. Pls answer.
I don't see the point of creating different models for different sets. You can do that but then you will have to use separate models when it comes to implementing. I recommend training all images to create a single model that potentially works on any image.
But sir how to use fixed number of features as SIFT gives different keynpoints for every image. And for 40x40 image SIFT give very small keynpoints. Kindly make a.video for such small image with SIFT. Or we have to use some.other feature extraction for such small images. If yes then what are the features extractor and how to use them. Pls
Great work. Is this the way to calculate the nucleus Hematoxylin OD? I am looking for extraction of the nucleus Hematoxylin OD, I would be grateful if you point me in the right direction.
Thank you a lot for this good material. But I am facing a memory error when I tried to normalize a WSI at the highest resolution (level 0) with a size around 40k x 55k. I tried to follow a sliding window approach and normalize each patch but the results are not good. Can you please suggest a workaround to solve this issue?
@@DigitalSreeni Thanks very much for the reply, I am using openslide to read the WSI's patches, then apply the normalization on them but when I stitch them together I end up with inconsistent behavior of the normalization. Can I do this stain operation on the fly when I generate the patches to feed the model? but then it will not be computed with respect to the whole slide? Thanks again for the support
wow, just found this channel and the content is amazing! Question, would it be possible to "delete" a stain from the original image? For example if I wanted to remove the eosin expression. Cheers!
Wouldn't that be just converting image from color to gray? I may have misinterpreted your question. The process from this video normalizes H&E and also separates H and E contributions. If you want to remove Eosin then just convert the separated Eosin image to gray and mix it back with the H image.
You are totally correct. The thing is that I am splitting into three stains instead of two, but the solution is the same... just convert the specific stain to gray and stack the stains. Thanks!
There is no existing python library for photo bleaching correction. You have to literally read published algorithms and write python code. This is a lot of development work and usually done during research process. For quick solution please use ImageJ or your manufacturer software. Hopefully someone publishes a library that we can use.
Not really. I try to focus on technology and illustrate using application knowledge I have which is in many fields but not much in immunohistochemistry. I only know basics like converting RGB to HED.
I am learning all about image analysis using python with your channel! Your tutorials are amazing! Great work to the scientific community! Thanks a lot!
Great to hear!
Wow....that works amazing with my fibrotic tissue images!
Just out of the box near perfect results in separating healthy from fibrotic tissue!
Keep your tutorials coming!
Best wishes from Germany!
Thank you very much. I am glad it worked out of the box, rarely happens :)
I must try this on my Sirius Red sections!
Great Work! I'm so thank you. Your channel is quite helpful for my thesis. Please continue related to H&E images apps.
Very interesting video always like your way of explaining and simplifying things well done. I am working on a large histopathology brain tumor image svs format is there any way to normalize those large images?. I tried to export tiles from those large images using qupath and tried individual tile on the python code you presented to normalize it it worked but not sure how can I normalize too many tiles images(1000 and above) at once ?.
the new video is just for u. see also:
digitalslidearchive.github.io/HistomicsTK/examples/color_normalization_and_augmentation.html
never tested personaly, but if u could make it work let me know pls
Hi DigitalScreeni! Thank you for the video. I was just going though the paper and there is one thing I do not understand. Why do you use in your code the refence matrix HERef? An where does it come from? As far as I can tell there is no mention of the reference mixing matrix in the paper. Is it not the point of the paper to automatically determine the stain vectors so that no pre-determined matrices need to be used? I am confused.
Nice video Sreeni. Really benefiting my work! One question: How would it be possible to remove noise particularly these histology slides? Applying Filters? Keep up the good work!
Please watch my video #22.
Hello Sir, great video. Does the color normalization method, that has been used there in MATLAB, work on malaria slide images as well??
I am not familiar with MATLAB functionality. This video shows the normalization process of H&E stained images and it shouldn't matter what type of sample as long as it is H&E stained.
@@DigitalSreeni Thank you Sir, for your response I will look into it.
I really appreciate your efforts. Keep up the good work!!
Thanks a lot!
Great work, Appreciated.
Amazing great, Thank you very much
I have tried this with MITOS ATYPIA14 dataset which are fully H&E stained images but nuclei segmentation using watershed algorithm isn't working properly. What to do?
Thanks for your hard work. Could you consider doing colocalization analysis?
That is a tough one :) It is easy to find existing libraries and use its functionality. It is very time consuming to write code for big algorithms, usually part of thesis work. Let us hope someone creates a library that we can use.
very helpful Video !! Thank you !
Thank you so much. I found this video very informative
Great work....! Thanks for upload this vedio ...
Thank you Sreeni sir! It's very helpful!
Most welcome!
Great work! How can I cite u, if i using your tutorials in papers or my phd work?
Thanks. Please don't worry about citing me, I am doing this to educate people. Also, my videos do not have original research content that's worth citing. If you want to thank then you can cite this RUclips channel.
I am getting this type of error "cannot do a non-empty take from an empty axes in numpy" when passing multiple images.Plz help me out
Hello sir. I have 20 different types of English alphabets images. In each type there are total 2000 images of all alphabets. That means set one has all englisgbalphabetsband it contains 2000 images. So the total database is of 40000 images. So should I use different classification model for each set out of 20 or I should use all.40000 images in one model. I want to use machine learning not deep learning. Pls answer.
I don't see the point of creating different models for different sets. You can do that but then you will have to use separate models when it comes to implementing. I recommend training all images to create a single model that potentially works on any image.
But sir how to use fixed number of features as SIFT gives different keynpoints for every image. And for 40x40 image SIFT give very small keynpoints. Kindly make a.video for such small image with SIFT. Or we have to use some.other feature extraction for such small images. If yes then what are the features extractor and how to use them. Pls
Great work. Is this the way to calculate the nucleus Hematoxylin OD? I am looking for extraction of the nucleus Hematoxylin OD, I would be grateful if you point me in the right direction.
Qupath allows you to do that
how is this different from reinhard, macenko normalizations
Thank you so much
Is there any benefit of creating binary masks of H stain and furthering the task to segment using Unet
This is one of the common workflows in digital pathology; after normalization segmenting all nuclei and generating reports based on measurements.
Thank you a lot for this good material. But I am facing a memory error when I tried to normalize a WSI at the highest resolution (level 0) with a size around 40k x 55k. I tried to follow a sliding window approach and normalize each patch but the results are not good. Can you please suggest a workaround to solve this issue?
For WSI, you have to apply operations to individual tiles extracted using openslide or some other library.
@@DigitalSreeni Thanks very much for the reply, I am using openslide to read the WSI's patches, then apply the normalization on them but when I stitch them together I end up with inconsistent behavior of the normalization. Can I do this stain operation on the fly when I generate the patches to feed the model? but then it will not be computed with respect to the whole slide? Thanks again for the support
wow, just found this channel and the content is amazing! Question, would it be possible to "delete" a stain from the original image? For example if I wanted to remove the eosin expression. Cheers!
Wouldn't that be just converting image from color to gray? I may have misinterpreted your question. The process from this video normalizes H&E and also separates H and E contributions. If you want to remove Eosin then just convert the separated Eosin image to gray and mix it back with the H image.
You are totally correct. The thing is that I am splitting into three stains instead of two, but the solution is the same... just convert the specific stain to gray and stack the stains. Thanks!
can I used this method in my paper to publish with citation to the original paper?
Sure.
thanks for the tutorial. can you show us how we can perform photobleaching correction and object tracking using python?
There is no existing python library for photo bleaching correction. You have to literally read published algorithms and write python code. This is a lot of development work and usually done during research process. For quick solution please use ImageJ or your manufacturer software. Hopefully someone publishes a library that we can use.
Any videos for immunohistochemistry stained tissues?
Not really. I try to focus on technology and illustrate using application knowledge I have which is in many fields but not much in immunohistochemistry. I only know basics like converting RGB to HED.
@@DigitalSreeni That's fine - thank you for sharing your knowledge with the world!