The following jupyter notebook was published on github .
The aim is to generate a large dataset of overlapping chromosomes (grey scaled image + ground truth label image) to train a neural network to perform semantic segmentation on such images.
To gain a large number of images the resolution was decreased by 16. A first try proposed in the ai.on project seems to do a very good job. The results was obtained from a dataset of 13434 pair of images from a python implementation of Unet.
To gain a large number of images the resolution was decreased by 16. A first try proposed in the ai.on project seems to do a very good job. The results was obtained from a dataset of 13434 pair of images from a python implementation of Unet.
