here are 45 research papers with code for medical image segmentation : https://paperswithcode.com/task/medical-image-segmentation
according to you which one is most powerful and why?
Very interesting approach. Instead of doing the work you need to do, you ask other people on researchgate.net to do it for you.
So, you go swimming and wait in the shade while other sweat and work.
Tell us if you find anybody wanting to do this for free.
Why would they?
This leads to a classical question in Economics Research: exploitation of work force, paid and unpaid labour.
:)
In my opinion, when deep learning techniques are involved in any approach; it should be useful, practical and robust. The main difficulty here is to train the ANN, and to find the appropriate datasets.
Can you tell me how to transform a code into a fiji/image j plug in?
Then I can tell you which one seems to work best.
I'd deeply appreciate that.
Thank you very much.
Dear Mitchell Wachtel i don't know.i am working on kaggle pneumothorax segmentation challenge,as a deep learning starter i am using mask rcnn,unet with efficientnet encoder,densenet and ensembling for that kaggle competition,i have no idea about how to transform a code into a fiji/image j plug in ,sorry!
Hi Mitchell, you must to write it in Java. You can eclipse or IntelliJ as IDE.
It isn't very difficult if you have programming knowledge. If you need help you can write me directly
more info: https://imagej.net/Writing_plugins
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