Locating model generation method and spinal sagittal image processing method

Abstract

The invention discloses a locating model generation method, a method for performing skeleton locating on a spinal sagittal image, and a computing device used for executing the methods. The locating model generation method comprises the steps of obtaining the tagged spinal sagittal image to serve as a training image, wherein the training image has corresponding tagged data; inputting the training sample to a pre-trained locating model for performing processing, wherein the locating model comprises a convolution processing layer, a classification processing layer and a regression processing layer, the convolution processing layer performs convolution, activation and pooling processing on the input image to output at least one located skeleton, and the classification processing layer and theregression processing layer perform classification processing and regression processing on the located skeleton respectively to output a probability of predicting that the skeleton belongs to sacrum and a predicted position of the skeleton; and according to the tagged data, performing model training on the pre-trained locating model to obtain a trained locating model.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method for generating a positioning model and a method for processing a spine sagittal image. Background technique [0002] With the rapid development of computer technology and image processing technology, the use of computer technology to assist orthopedic precision surgery is gradually increasing. The most common application is Magnetic Resonance Imaging (MRI) imaging, from which a variety of physical property parameters of matter can be obtained, such as proton density, spin-lattice relaxation time T1, spin-spin Spin relaxation time T2, diffusion coefficient, magnetic susceptibility coefficient, chemical shift, etc., in order to apply it to the imaging diagnosis of various systems of the whole body. One of the main applications is spinal imaging to obtain sagittal images of the human spine, which can then be used in the diagnosis of various spinal diseases, such a...

AI Technical Summary

Problems solved by technology

However, there are still some shortcomings in the process of using MRI images to diagnose spinal diseases. For example, under the condition of interference, the image quality is not good, and the positioning of bone marker points is still based on the naked eye judgment, which needs to rely on the experience of doctors. and image quality, this approach is both error-prone and labor-intensive

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