Diagnosis model constructed based on artificial intelligence fusion multi-modal information and used for various pathology types of benign and malignant pulmonary nodules
A technology of artificial intelligence and diagnostic models, applied in the field of medical image processing, can solve problems such as low work efficiency, high dependence on personal clinical experience, and inability to classify and diagnose pulmonary nodules pathological types, and achieve the effect of improving diagnostic efficiency
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[0028] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific implementation. The present invention realizes the construction of multiple pathological types of benign and malignant pulmonary nodules diagnostic models based on artificial intelligence fusion of multiple modal information mainly including the following steps:
[0029] S1 builds a multi-resolution 3D multi-category deep learning network model.
[0030] S1.1 Collect CT image data with clear pathological types, and the slice thickness is 1mm.
[0031] Collect CT image data of four pathological types, including inflammation, squamous cell carcinoma, adenocarcinoma, and benign others. It is required to have a clear pathological type, and the layer thickness is 1mm, and the diameter D of the nodule is 3mm≤D≤30mm. It is divided into training set, verification set and test set according to the proportion of categories.
[0032] S1.2 Extract and store t...
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