Faimed3d - fastai extension for volumetric medical data

Deep Learning
22

Hi,

my initial motivation was to implement tools for radiological images into fastai and then I decided to share it with the community, hoping it will be helpful.

I have also made some papers with the library:

However, today I mostly use MONAI and faimed3d is not actively developed anymore.
I love fastai, but for 3D medical imaging MONAI provides the better tools.

2 Likes
23

Those are great publications ā€¦ Kudos!
I am keen to hear your thoughts on MONAI. I gave it a brief glance but am biased towards fastai. I have been writing some code to extend it somewhat. Have a look at my post Code collaboration opportunity for radiology projects (KiTS)

I have been able to do most things with fastai+pytorch, using torchio etc here and there, but am keen to hear where MONAI really outshines fastai.

Thanks
Usman

1 Like
24

The main reason is, that fastai is designed for 2d images and does this really well. However, 3D data, such as CT or MRI come with additional challenges. One of my main reasons to switch to MONAI were:

  1. They have 3D models, which are not provided by fastai. I have written some 3D models in faimed3d, but MONAI offers a much greater variety.
  2. CT/MRI require specific transforms, such as simulation of typical artifacts. One can use torchio but, AFAIK, torchio is not under active development anymore, instead the creator joined MONAI.
  3. MONAI provides better support of medical data and special data loaders with caching. This is important, as DICOM is often compressed, making the dataloader the bottleneck of your training.

I still use fastai for 2D images, as the training routines are better and I find it really easy to use. However, my main work nowadays is on 3D data. Similar to you, Iā€™ve also written a training routine for segmentation :smiley: using MONAI and ignite, but its WIP GitHub - kbressem/trainlib: Template for MONAI projects

1 Like
25

Yes Monai is very very polished. I am just so in love with the fastai coding philosophy that I found it near impossible to break from it. Please keep me updated on any interesting things you find along the way :+1:

26

Any hints where I can find some work on generative models for medical images (dsa brain arteries)?

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What do you have in mind specifically?

There is something like: https://arxiv.org/pdf/2210.04133.pdf (ā€œAdapting Pretrained Vision-Language Foundational Models to Medical Imaging Domainsā€)

Or something like this: Deep-Learning Generated Synthetic Double Inversion Recovery Images Improve Multiple Sclerosis Lesion Detection - PubMed

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or this: [2209.07162] Brain Imaging Generation with Latent Diffusion Models
They even open sourced their generated data.

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This looks great! Is it easy to adapt to support regression problems?

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Just to clarify, I havenā€™t joined MONAI :smiley: