An automatically produced abdominal segmentation produced by the toolkit (contours each organ in the abdomen and identifies it with a specific label/colour)
The Deep Learning Tool Kit (DLTK) for Medical Imaging comes back with a new, simpler version and a model zoo.
DLTK is a neural networks toolkit written in python, on top of TensorFlow. It is developed to enable fast prototyping with a low entry threshold and ensure reproducibility in image analysis applications, with a particular focus on medical imaging.
Its goal is to provide the community with state of the art methods and models and to accelerate research in this exciting field.
Examples of use of DLTK for medical applications are:
as well as a simple GANs.
A closer look at the abdominal segmentation from a CT scan
DLTK has performed well in multiple AI competitions (think Kaggle but for academics):