The invention provides a
lung cancer pleural invasion auxiliary diagnosis
system and method based on a multiphoton
microscopy technology, and belongs to the technical field of medical
artificial intelligence and intraoperative
pathology assistion.The method comprises the steps that multiphoton images of unstained paraffin sections, frozen sections and
fresh tissue are collected through the multiphoton
microscopy system; constructing a multi-
source data set and extracting 142-dimensional tissue features; after cross-domain data enhancement of the
generative adversarial network, semantic features extracted by the
deep learning pre-training model are fused, and a pleura infringement state classifier is constructed; in the operation, a real-time image is obtained through a portable multi-
photon system and input into a classifier to rapidly predict VPI negative and positive. According to the method, rapid, accurate and
label-free diagnosis in the operation of the VPI is realized, real-time support is provided for decision-making of the resection range of the
lung cancer operation, insufficient treatment or excessive resection is avoided, and the prognosis of a patient is effectively improved.