Gynecological cyst excision operation auxiliary instrument and method
A technology for gynecological cysts and cysts, which is applied in the field of medical devices and can solve problems such as poor image quality of cysts, noise, and inaccurate monitoring of cyst rupture data.
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Embodiment 1
[0070] The gynecological cyst excision operation auxiliary method provided by the embodiment of the present invention is as follows: figure 1 As shown, as a preferred embodiment, such as image 3 As shown, the image enhancement method provided by the embodiment of the present invention is as follows:
[0071] S201, acquiring cyst image data during the microsurgery; editing the cyst image data; recording information related to the cyst image data, the information including real-time vital sign information of the patient during the microsurgery ; Store the edited cyst image data and recorded information;
[0072] S202. Select a first color space and a second color space to be operated; set a first parameter range of the first color space and a first cyst image enhancement process corresponding to the first parameter range; set the second color The third parameter range of the space and the third cyst image enhancement processing corresponding to the third parameter range;
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Embodiment 2
[0083] The gynecological cyst excision operation auxiliary method provided by the embodiment of the present invention is as follows: figure 1 As shown, as a preferred embodiment, such as Figure 4 As shown, the cyst rupture monitoring method provided by the embodiments of the present invention is as follows:
[0084] S301. Obtain a standard longitudinal section image of the uterus; analyze the standard longitudinal section image of the uterus using an endometrium typing model; acquire ruptured endometrioma cyst data and unruptured endometrioma cyst data to form sample data , and normalize the obtained sample data, and further divide the normalized sample data into a test set and multiple training sets;
[0085] S302, select the decision tree type as CART, carry out decision tree training on each training set respectively, and obtain the corresponding CART decision tree model trained by each training set; for each CART decision tree model, compare and select through the Gini i...
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