The invention discloses a
deep learning-based
stroke prognosis prediction method and
system. The method comprises the steps of obtaining a head magnetic
resonance medical image
data set of a
stroke patient before treatment and a corresponding mRS
score of
stroke prognosis; segmenting a core
infarction focus image from the obtained magnetic
resonance medical image by adopting a DWI sequence; establishing a six-
score cSVD load scoring standard, scoring the core
infarction focus image, and constructing a model
data set; 3, constructing a prediction model for predicting the stroke prognosis mRS
score, dividing the model
data set in the step 3 into a
training set, a
verification set and a
test set, training the prediction model by adopting the
training set, verifying the prediction model on the
verification set, testing by adopting the
test set, screening out the prediction model of which the precision meets the requirement, and determining the stroke prognosis mRS score. And predicting the mRS score of the stroke prognosis of the to-be-evaluated patient by adopting the screened prediction model. According to the method, the prediction capability of the image features obtained by MRI (
Magnetic Resonance Imaging) flat scanning of the LAA-AIS patient on prognosis is fully excavated, and a new reference direction is provided for prognosis evaluation of the LAA-AIS patient.