This invention provides an
automatic segmentation and scoring method and
system for lesions in
ischemic stroke of the
brainstem, including preprocessing
brain CT images;
automatic segmentation of the
brainstem; and acquisition of mirror
brainstem images and a brainstem atlas containing the
midbrain,
pons, and medulla oblongata regions. stem The method involves region segmentation of brainstem and mirror brainstem images; construction of a brainstem
infarction lesion detection and segmentation
network model; the brainstem
infarction lesion detection and segmentation
network model contains three encoders, one decoder, and six difference calculation modules. Each
encoder consists of three convolutional
layers, each decoder consists of three deconvolutional
layers, and the difference calculation module includes multi-scale
pyramid convolutions and
feature fusion modules at each scale; prediction scoring is performed based on the segmented lesions. The
lesion detection and segmentation method of this invention can quickly, accurately, and objectively detect and segment lesions.