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Spine CT sequence image segmentation method and system

A sequential image and spine technology, applied in the field of CT sequence image segmentation, can solve the problems of increasing the burden of kidney metabolism, allergic reaction of contrast medium, high risk, etc., and achieve the effect of accurate and reliable segmentation results, accurate segmentation results, and reduced burden

Pending Publication Date: 2020-06-09
刘华清
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Problems solved by technology

However, this method of contrast agent enhancement will increase the burden of renal metabolism, and the risk is higher for some patients with renal insufficiency, and some patients have allergic reactions to contrast agents

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  • Spine CT sequence image segmentation method and system
  • Spine CT sequence image segmentation method and system
  • Spine CT sequence image segmentation method and system

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Experimental program
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Embodiment

[0047] like figure 1 As shown, a spine CT sequence image segmentation method, the method includes a training phase and a testing phase,

[0048] The training phase includes the following steps:

[0049] (A1) Manual labeling: Obtain multiple sets of CT sequence images, and perform manual semantic segmentation on bony structures and various non-bone tissues in the CT sequence images to obtain manually labeled 3D mask images;

[0050] (A2) Dataset preprocessing: Preprocessing CT sequence images and their manually labeled 3D mask images to construct a global semantic segmentation dataset;

[0051] Locate and intercept the core segment of the spine in the CT sequence image and its artificially marked 3D mask image, and construct a local semantic segmentation dataset;

[0052] (A3) Construct a global semantic segmentation network and a local semantic segmentation network;

[0053] (A4) Using the preprocessed global semantic segmentation dataset to train the global semantic segmen...

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Abstract

The invention relates to a spine CT sequence image segmentation method and system, the method comprises a training stage and a test stage. The training stage comprises the following steps: (A1) carrying out manual annotation, (A2) preprocessing a data set, (A3) constructing a global semantic segmentation network and a local semantic segmentation network, and (A4) training the global semantic segmentation network and the local semantic segmentation network. The test stage comprises the following steps: (B1) acquiring a CT sequence image to be segmented, (B2) carrying out image preprocessing, (B3) performing global semantic segmentation on a bony structure and a non-bony tissue in the CT sequence image, (B4) carrying out local semantic segmentation on various non-bony tissues in the spine core section, and (B5) synthesizing and obtaining a segmentation result. Compared with the prior art, the method can achieve the quick and automatic segmentation of the bone structure and various typesof non-bone tissues in the spine CT sequence image, and is accurate and reliable in segmentation result.

Description

technical field [0001] The present invention relates to a CT sequence image segmentation method and system, in particular to a spine CT sequence image segmentation method and system. Background technique [0002] Spinal surgery is being carried out in full swing all over the world due to its small incision and less damage. Accurate surgical planning is the key to the success of spinal surgery, and various medical imaging technologies are the cornerstone of preoperative planning for spinal surgery. The planning of conventional spinal surgery relies heavily on the subjective experience of the surgeon, precisely because the objective information provided by conventional medical imaging is not comprehensive enough. Currently, spine surgeons mainly rely on traditional two-dimensional images, including plain X-rays, CT, and MRI, to formulate surgical plans. X-rays can quickly provide two-dimensional information on the bony structure of the spine, which has important clinical valu...

Claims

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Application Information

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IPC IPC(8): G06T7/10G06T7/00G06N3/08
CPCG06N3/08G06T7/0012G06T7/10G06T2207/10081G06T2207/20081G06T2207/30012
Inventor 刘华清
Owner 刘华清
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