Multi-task learning framework for fully automatic assessment of coronary artery disease

The invention relates to a multi-task learning framework for fully automatic assessment of coronary artery disease. Systems and methods for automated evaluation of a vessel 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 using multi-task learning. The plurality of vessel evaluation tasks are performed by the machine learning-based model based on shared features extracted from the one or more input medical images. And outputting results of the plurality of vessel evaluation tasks or a combination of the results of the plurality of vessel evaluation tasks. 本公开涉及用于对冠状动脉疾病进行全自动评估的多任务学习框架。提供了用于对脉管进行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，所述基于机器学习的模型是使用多任务学习来训练的。所述多个脉管评估任务是由所述基于机器学习的模型基于从所述一个或多个输入医学图像中提取的共享特征来执行的。输出所述多个脉管评估任务的结果或所述多个脉管评估任务的结果的组合。