Automatic artery-vein name identifying method which is based on conditional random fields and used for gastric-carcinoma endoscope operation real-time navigation system
A technique of conditional random field and endoscopic surgery, applied in the fields of machine learning, minimally invasive surgery, and imaging, can solve the problem of difficulty in extracting the three-dimensional structure of blood vessels, shorten the length of hospital stay, reduce complications, and reduce hospitalization The effect of fees
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[0018] The method for automatically identifying arteriovenous names based on conditional random fields in the real-time navigation system for gastric cancer laparoscopic surgery according to the present invention, such as figure 1 Shown:
[0019] 1. Data collection:
[0020] Establish criteria such as (a) pathologically confirmed primary completely resectable gastric cancer patients; (b) preoperative clinical stage: T1-4aN0-3M0; (c) abdominal enhancement less than 15 days before operation CT.
[0021] The influence of other factors on this experiment was excluded.
[0022] 2. Construction of the original 3D model:
[0023] The preoperative CT image is segmented, marked, and modeled to obtain a virtual blood vessel model.
[0024] (1) CT scan:
[0025] The patient fasted for more than 6 hours, took 500ml of warm water orally to fill the intestinal tract half an hour before the scan, and took 500ml of warm water to fill the stomach and duodenum 5 minutes before the scan.
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