| CPC G06T 7/0012 (2013.01) [A61B 6/505 (2013.01); A61B 6/5217 (2013.01); G06T 7/11 (2017.01); G16H 30/40 (2018.01); G16H 50/30 (2018.01); G06T 2207/20084 (2013.01); G06T 2207/30012 (2013.01)] | 16 Claims |

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1. A method for automatic assessment of spine health, the method comprising:
receiving a medical image of at least a portion of a spine in a patient;
supplying the medical image to a deep learning network trained using a plurality of training spine images and, for each training spine image, one or more spine measurement annotations, wherein supplying the medical image to the deep learning network includes supplying the medical image to a feature generation network that performs convolutions and produces, as outputs, learnable features;
providing the outputs from the feature generation network to a region recognition network that produces, as output, an objectness logits map showing a probability of an approximate region containing an object;
combining the features and the objectness logits map to produce a combined output from the region recognition network and providing the combined output to a landmark network;
detecting, using the landmark network, five or more vertebral landmarks for each of a plurality of vertebral bodies depicted in the medical image; and
outputting, for at least a first vertebral body, one or more deformity measurements based on the vertebral landmarks for the first vertebral body.
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