| CPC A61B 8/5261 (2013.01) [A61B 8/14 (2013.01); A61B 8/4254 (2013.01); A61B 8/4488 (2013.01); A61B 8/463 (2013.01); A61B 8/466 (2013.01); G06T 7/11 (2017.01); G06T 7/30 (2017.01); G06T 7/70 (2017.01); G06T 2200/04 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/30004 (2013.01)] | 4 Claims |
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1. A method, comprising:
defining a standardized three dimensional coordinate system for a plurality of three dimensional reference images of corresponding regions of interest (ROIs) in a plurality of subjects, wherein the three dimensional reference images were obtained using a first imaging modality;
for each of the plurality of subjects:
obtaining a series of spatially tracked two dimensional acoustic images of the ROI in the subject;
constructing a three dimensional acoustic image of the ROI in the subject from the series of spatially tracked two dimensional acoustic images of the ROI, wherein the three dimensional acoustic image of the ROI in the subject is in an acoustic three dimensional coordinate system;
accessing a selected three dimensional reference image among the plurality three dimensional reference images, wherein the selected three dimensional reference image is of the ROI in the subject;
segmenting the three dimensional reference image of the ROI in the subject;
defining a reference three dimensional coordinate system for the reference image of the ROI in the subject, based on the segmentation; and
determining for each of the spatially tracked two dimensional acoustic images of the ROI in the subject its actual pose in the standardized three dimensional coordinate system using: a pose of the spatially tracked two dimensional acoustic image in the acoustic three dimensional coordinate system, a first coordinate transformation from the acoustic three dimensional coordinate system to the reference three dimensional coordinate system, and a second coordinate transformation from the reference three dimensional coordinate system to the standardized three dimensional coordinate system; and
performing an optimization process on a convolutional neural network (CNN) by providing the spatially tracked two dimensional acoustic images, and the corresponding actual poses of the spatially tracked two dimensional acoustic images, to the CNN and adjusting parameters of the CNN to minimize differences between predicted poses generated by the CNN for the spatially tracked two dimensional acoustic images and the actual poses of the spatially tracked 2D acoustic images.
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