Extraction of Airways using Graph Neural Networks
Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning › fagfællebedømt
We present extraction of tree structures, such as airways, from image data as a graph refinement task. To this end, we propose a graph auto-encoder model that uses an encoder based on graph neural networks (GNNs) to learn embeddings from input node features and a decoder to predict connections between nodes. Performance of the GNN model is compared with mean-field networks in their ability to extract airways from 3D chest CT scans.
|Status||Udgivet - 2018|
|Begivenhed||1st International conference on Medical Imaging with Deep Learning - Amsterdam, Holland|
Varighed: 4 jul. 2018 → 6 jul. 2018
|Konference||1st International conference on Medical Imaging with Deep Learning|
|Periode||04/07/2018 → 06/07/2018|