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updating readme
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ctr26 committed Aug 26, 2023
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pip install git+https://github.com/ctr26/bioimage_embed



# Mask-VAE

This project attempts to using modern auto-encoding CNNs to access the latent shape space of a given dataset.
We demonstrate this on microscopy images of nuclei and C. Elegans (worms).
The project includes some sensible tricks such as including symmetry $\min|M^T - M|_2^2$ and $\min|diag(M)|$ constraints to help the model learn that it's using distance matrices.

## How it works

- Take image masks (white on black)
- Find their contour (thx [scikit image]((https://scikit-image.org/docs/dev/api/skimage.measure.html#skimage.measure.find_contours)))
- Resample the contour to a standard length
- Create euclidean distance matrix
- Feed matrix as image into VAE
- Train model on distance matrix
- Opt. Convert distance matrix back to mask using MultiDimensionalScaling

Potential uses for this projects are:

- Synthetic shape generation for dataset augmentation
- Shape-based phenotyping in the latent space

## Usage

### Get data
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### Run

python train.py
bioimage_embed --help

or

bie --help

### TODO

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