Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation

Understand

Incorporation of prior knowledge about organ shape and location is key to improve performance of image analysis approaches.

• In particular, priors can be useful in cases where images are corrupted and contain artefacts due to limitations in image acquisition.
• The highly constrained nature of anatomical objects can be well captured with learning based techniques.
• However, in most recent and promising techniques such as CNN based segmentation it is not obvious how to incorporate such prior knowledge.