Systems and methods for determining blood vessel conditions

A system for evaluating a blood vessel, comprising:

• a processor, configured to:
• receive image data of the blood vessel acquired by an image acquisition device;
• and
• predict blood vessel condition parameters of the blood vessel by applying a deep learning model to the acquired image data of the blood vessel, wherein the deep learning model maps a sequence of image patches on the blood vessel to blood vessel condition parameters on the blood vessel, wherein the deep learning model includes a convolutional neural network, a recursive neural network, and a conditional random field model connected in series, wherein parameters of the convolutional neural network, the recursive neural network, and the conditional random field model are jointly optimized;
• and
• a display configured to display the blood vessel condition parameters of the blood vessel for evaluating the blood vessel.

A non-transitory computer readable storage medium storing computer executable instructions thereon, which, when executed by a processor, implement a method for evaluating a blood vessel, comprising:

• receiving image data of the blood vessel acquired by an image acquisition device;
• predicting, by a processor, blood vessel condition parameters of the blood vessel by applying a deep learning model to the acquired image data of the blood vessel, wherein the deep learning model maps a sequence of image patches on the blood vessel to blood vessel condition parameters on the blood vessel, wherein the deep learning model includes a convolutional neural network, a recursive neural network, and a conditional random field model connected in series, wherein parameters of the convolutional neural network, the recursive neural network, and the conditional random field model are jointly optimized;
• and
• providing the blood vessel condition parameters of the blood vessel for evaluating of the blood vessel.