A system and method for evaluating a cardiac region of a subject

In an electronic image processing system, a method of evaluating a cardiac region of a subject, from 2.5D, 3D or 4D medical image data, by using a trained machine learning data processing model, wherein the trained machine learning data processing model is trained to predict cardiac characteristics of the cardiac region of the subject, the method comprising:

• receiving, by a controller, the medical image data;
• providing the medical image data to the trained machine learning data processing model for predicting, using the trained machine learning data processing model, cardiac characteristics of the cardiac region of the subject, wherein the medical image data is associated with a lifecycle parameter indicating a first moment in time of the subject;
• and
• predicting, by the trained machine learning data processing model, the cardiac characteristics of the cardiac region at a second moment in time, wherein the second moment in time is subsequent to the first moment in time.

A method of training a machine learning data processing model for determining cardiac characteristics of a cardiac region of a subject from 2.5D, 3D or 4D medical image data, the method comprising the steps of:

• a) receiving, by the machine learning data processing model, a training data set comprising training data, the training data including image data of a plurality of images;
• b) receiving, by the machine learning data processing model, a ground truth data set comprising ground truth data indicative of a ground truth cardiac characteristic that matches with the image data of the plurality of images of the training data;
• and
• c) training the machine learning data processing model based on the training data received in step a) and the ground truth data received in step b), for enabling the machine learning data processing model, after completion of the training period, to perform the step of determining the cardiac characteristics of the cardiac region of the subject.

An electronic image processing system comprising a trained machine learning data processing model, for predicting cardiac characteristics of a cardiac region of a subject from 2.5D, 3D or 4D medical image data, wherein the system further comprises one or more processors and a memory storing the trained machine learning data processing model and one or more instructions, which when loaded into the memory enable the one or more processors to perform the steps of:

• receiving, by a controller, the medical image data;
• providing the medical image data to the trained machine learning data processing model for predicting, using the trained machine learning data processing model, cardiac characteristics of the cardiac region of the subject;
• wherein the medical image data is associated with a lifecycle parameter indicating a first moment in time of the subject;
• and
• predicting, by the trained machine learning data processing model, the cardiac characteristics of the cardiac region at a second moment in time, wherein the second moment in time is subsequent to the first moment in time.