Medical imaging based on calibrated post contrast timing

A non-transitory computer-readable medium carrying one or more sequences of instructions for measuring post contrast phase, wherein execution of the one or more sequences of instructions by one or more processors causes the one or more processors to perform at least the following:

• collect three dimensional (3D) medical imagery of a subject using a 3D medical imaging device after the subject is injected with a contrast agent;
• obtain a first set of one or more slices displaced in the axial direction, wherein each slice in the set includes a first anatomical feature selected from a group consisting of an aorta, a portal vein, an inferior vena cava, a liver, a spleen and a renal cortex;
• obtain a second set of one or more slices displaced in the axial direction, wherein each slice in the second set includes a different second anatomical feature selected from the group;
• obtain a first image region on a first slice of the first set and a different second image region on a second slice of the second set, wherein the first image region includes the first anatomical feature and the second image region includes the different second anatomical feature;
• use a first trained convolutional neural network with input based on the first image region and the second image region, configured to determine a post contrast phase, wherein the first trained neural network comprises:
• a first plurality of convolutional hidden layers operating on the first image region;
• a second plurality of convolutional hidden layers operating on the second image region;
• and
• at least one fully connected hidden layer receiving output from both the first plurality of convolutional hidden layers and the second plurality of convolutional hidden layers, and outputting to an output layer of one or more nodes corresponding values each representing a probability of a post contrast phase;
• and
• present automatically, on a display device, output data based on the post contrast phase.

A system for measuring post contrast phase comprising:

• a three dimensional (3D) medical imaging device;
• a display device;
• at least one processor;
• and
• at least one memory including one or more sequences of instructions,
• the at least one memory and the one or more sequences of instructions configured to, with the at least one processor, cause the apparatus to perform at least the following,
• collect 3D medical imagery of a subject using the 3D medical imaging device after the subject is injected with a contrast agent;
• obtain a first set of one or more slices displaced in the axial direction, wherein each slice in the first set includes a first anatomical feature selected from a group consisting of an aorta, a portal vein, an inferior vena cava, a liver, a spleen and a renal cortex;
• obtain a second set of one or more slices displaced in the axial direction, wherein each slice in the second set includes a different second anatomical feature selected from the group;
• obtain a first image region on a first slice of the first set and a second image region on a second slice of the second set, wherein the first image region includes the first anatomical feature and the second image region includes the different second anatomical feature;
• use a first trained convolutional neural network with input based on the first image region and the second image region, configured for determining a post contrast phase,
• wherein the first trained neural network comprises:
• a first plurality of convolutional hidden layers operating on the first image region;
• a second plurality of convolutional hidden layers operating on the second image region;
• and
• at least one fully connected hidden layer receiving output from both the first plurality of convolutional hidden layers and the second plurality of convolutional hidden layers, and outputting to an output layer of one or more nodes corresponding values each representing a probability of a post contrast phase;
• and
• present on the display device, output data based on the post contrast phase.

An apparatus configured as a trained neural network for measuring post contrast phase comprising:

• a first plurality of convolutional hidden layers operating on a first image region that includes a first anatomical feature selected from a group consisting of an aorta, a portal vein, an inferior vena cava, a liver, a spleen and a renal cortex;
• a second plurality of convolutional hidden layers operating on a different second image region that includes a different second anatomical feature selected from the group;
• and
• at least one fully connected hidden layer receiving output from each of the first plurality of convolutional hidden layers and the second plurality of convolutional hidden layers and outputting to an output layer one or more nodes each representing a probability of a post contrast phase.