Coronary artery segmentation from intravascular optical coherence tomography using deep capsules
作者：
Highlights：
• Deep learning method based on capsules to segment coronary artery lumens (DeepCap).
• Inputs are intravascular optical coherence tomography images in Cartesian form.
• DeepCap is a robust lightweight model specifically designed for clinical utility.
• Model was built, validated and tested using >12,000 images that include artefacts.
• Performance is on-par with other methods, yet needs 88 % less parameters.
摘要
•Deep learning method based on capsules to segment coronary artery lumens (DeepCap).•Inputs are intravascular optical coherence tomography images in Cartesian form.•DeepCap is a robust lightweight model specifically designed for clinical utility.•Model was built, validated and tested using >12,000 images that include artefacts.•Performance is on-par with other methods, yet needs 88 % less parameters.
论文关键词：Capsule network,Coronary artery,Deep learning,Optical coherence tomography
论文评审过程：Received 19 August 2020, Revised 6 April 2021, Accepted 7 April 2021, Available online 15 April 2021, Version of Record 23 April 2021.
论文官网地址：https://doi.org/10.1016/j.artmed.2021.102072
