The title of the invention is an MRI spinal image keypoint detection method based on deep learning. Disclosed is an MRI spinal image keypoint detection method based on deep learning. The method comprises: firstly, detecting and positioning a vertebra in an MRI spinal image by using a deep target detection network, and identifying a sacrum 1 (S1) as a positioned vertebra; then, in conjunction with structural information of a spine, filtering false positive detection results and determining a fine-grained label of each vertebra; next, respectively detecting six keypoints in total, namely, UA, UM, UP, LA, LM and LP, on upper and lower borders of each vertebra by using a keypoint detection network; afterwards, in conjunction with edge information, determining and correcting a keypoint position of each vertebra; and finally, developing interactive visual MRI spinal image keypoint automatic annotation software. By means of the present invention, an MRI spinal image keypoint can be automatically extracted, which has immense application value in terms of medical image analysis, medical treatment assistance, etc.
MRI SPINAL IMAGE KEYPOINT DETECTION METHOD BASED ON DEEP LEARNING