The present application relates to a kind of
deep learning method based on SPECT / CT detection
thyroid-related
eye disease activity, including two stages of
eye muscle segmentation stage and activity staging classification, in the
eye muscle segmentation stage, first, the CT image of eye is three-dimensional reconstruction, and training
eye muscle semantic segmentation model, finally using the eye
muscle segmentation model of well-trained in
test set eye
muscle mask;In the classification stage of judging whether
thyroid-related
eye disease is in active period, three-
channel data are formed by using eye
muscle mask, SPECT and CT image, and three-
channel data are used to
train classification model, SPECT / CT image and the eye muscle
mask of patient are combined into three-channel image and input into classification model, and finally the activity of
thyroid-related
eye disease is output by the trained classification model.Through the
deep learning method of two stages, the activity of thyroid-related eye
disease is automatically classified.