Hi everyone,
I just wanted to announce that another engineer in the forum is now very much set to work with SimpleITK, I finally could get the Fiji viewer to work with python! Thanks for the forum documentation … uhhhhh… I now ready to fire my vtk-js/itk-js/itk/vtk/simpleitk/etc and doing hopefully great applications …
looking for good Deep learning material to test it with medical image processing anyone knows any good resources, please inform me,
regards
sag
It’s great to hear this!
If you are looking for medical imaging data sets to be used for deep learning then http://medicaldecathlon.com/ is a very good resource.
I would also add that if you work with Python Jupyter notebooks or 3D medical images then instead of Fiji you may consider 3D Slicer as image viewer/editor. By running 3D Slicer’s as Jupyter kernel you get all the features of a regular Python3 kernel (access to SimpleITK, ITK, VTK, etc.) but you can also visualize and modify images, segmentations, meshes, annotations, etc. in place (without launching an external viewer process and passing data through files), even inside Jupyter notebook. Interactive 3D data editing in Jupyter notebooks is very new and we are very excited about it and would love to get more feedback to see how people use it and how to improve things. You can find more information, video, online demo here.
Another website to check out medical dataset is https://grand-challenge.org/challenges/, you could filter out by modality, task type and structure etc. There are some datasets available on kaggle too.