Coronary lumen and reference wall segmentation for automated assessment of coronary artery disease

Systems and methods for automated evaluation of vessels are provided. One or more input medical images of a vessel of a patient are received. A plurality of vessel evaluation tasks for evaluating vessels are performed using a machine learning-based model trained by utilizing multi-task learning. The plurality of vessel evaluation tasks include segmentation of a reference wall of the vessel from the one or more input medical images and segmentation of a lumen of the vessel from the one or more input medical images. And outputting the results of the plurality of vessel evaluation tasks. 提供了用于脉管的自动评估的系统和方法。接收患者的脉管的一个或多个输入医学图像。使用通过利用多任务学习被训练的基于机器学习的模型来执行用于评估脉管的多个脉管评估任务。所述多个脉管评估任务包括从所述一个或多个输入医学图像对脉管的参考壁的分割以及从所述一个或多个输入医学图像对脉管的管腔的分割。输出所述多个脉管评估任务的结果。