CPC A61N 5/1031 (2013.01) [G06N 3/08 (2013.01); G16H 20/40 (2018.01); G16H 30/20 (2018.01)] | 20 Claims |
1. A computer-implemented method to predict a three-dimensional dose distribution, the method comprising:
receiving, with one or more processors, input data including a three-dimensional voxel image that includes two-dimensional slices, wherein each voxel in the three-dimensional voxel image includes a distance from the voxel to a closest organ surface in three-dimensional space;
providing at least a portion of the input data to a deep fully convolutional neural network (FCNN);
programmatically analyzing in parallel, by the one or more processors, two or more of the two-dimensional slices in the input data;
outputting, by the deep FCNN, a three-dimensional dose distribution prediction that includes a dose prediction for each of the two or more of the two-dimensional slices, wherein the dose prediction for each of the two or more of the two-dimensional slices is independent of dose predictions for other two-dimensional slices and wherein the dose prediction is based on the distance from corresponding voxels to the closest organ surface;
providing, by the one or more processors, the three-dimensional dose distribution prediction as output;
generating, by the one or more processors, a treatment plan based on the three-dimensional dose distribution prediction, wherein the treatment plan includes an electronic file that includes instructions to cause a radiotherapy system to treat a body of a patient associated with the three-dimensional voxel image using radiation; and
transmitting the treatment plan to the radiotherapy system for treatment of the patient associated with the three-dimensional voxel image, wherein the radiotherapy system applies radiation to the patient based on the treatment plan.
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