Pseudo Image Extraction

This repository extracts pseudo images from anatomical images for use in training convolutional neural networks.

Converts VTK models to png images for use by the CycleGAN model.

See options in export_config.py or by running create_seg_dataset.py -h

Extract pseudo images from anatomical models.

This repository is specifically designed for extracting images from cardiac models as described in Generating Synthetic Labeled Data from Anatomical Models: An Example with Echocardiography Segmentation. It may be used as a template for extracting image from other models as well.

The anatomical models from that paper are available here: https://zenodo.org/record/4590294#.YbfgcdDMLD4

The main script for extracting data is create_seg_dataset.py. Options are controlled at several different levels:

1. General options: These options include things such as the location of the model files, how many images should be extracted, what view (slice) should be extracted, how many images should be extracted, and some additional parameters. An overview of these parameters can be seen by running create_seg_dataset.py -h or looking at the argument parser defined in export_config.py.
2. View-specific options: These options define the specific model manipulations that are required for a given view. They are defined in a series of sub-steps which encompass movement transforms (getting the slice into the right orientation and position) and appearance transforms. Specific transforms can be defined for each view for each of these sub-steps in the get_view_specific_params() function in export_config.py.
3. Dataset-specific options: There may be cases where several parameters need to be defined for a given dataset. For example in the case of apical echocardiography images a dataset specific parameter might be the percentage of images that are focused on the left ventricle compared to the percentage of images focused on the whole heart.

Input

The input is a set of anatomical models. In particular the input for this project was a set of cardiac anatomical models. These models will be released pending a publication describing their development and a link to those models will be provided here once they are.

In particular this project also used an augmented set of models (see paper). A link to the augmented model set will also be provided.

An example model is shown above.

Output

The output of this step is a set of:

1. Pseudo-ultrasound images which contain slices from the model which match slices from real hearts observed in a set of real ultrasound images of the given view. An example for apical four chamber images is shown in the image below.
2. Labels for the pseudo-ultrasound images. These labels mark the relevant regions of the pseudo images and can be used when training a segmentation network. An example is shown below.

Install

Clone this repository and install the necessary requirements pip install -r requirements.txt.