CPC G06T 7/0012 (2013.01) [A61B 6/469 (2013.01); A61B 6/505 (2013.01); A61B 6/5217 (2013.01); G06F 18/213 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06T 7/11 (2017.01); G06T 7/73 (2017.01); G06V 10/44 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); G16H 50/30 (2018.01); G06T 2207/10116 (2013.01); G06T 2207/20072 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30012 (2013.01); G06T 2207/30052 (2013.01); G06T 2207/30168 (2013.01); G06V 2201/033 (2022.01)] | 18 Claims |
1. A computer-implemented method for radiographic bone mineral density (BMD) estimation, the method comprising:
receiving a plain radiograph;
detecting landmarks for a bone structure included in the plain radiograph;
extracting a region of interest (ROI) from the plain radiograph based on the detected landmarks, comprising:
detecting anatomical landmarks at a center of the femur head when detecting the landmarks included in the plain radiograph for the bone structure;
determining a size of the ROI relevant to a distance between two femur heads, wherein the ROI is a rectangular region containing a femur head, a greater trochanter, and a lesser trochanter, segmented from the plain radiograph; and
determining a center of the ROI based on locations of the femur heads; and
estimating the BMD for the ROI extracted from the plain radiograph by using a deep neural network.
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