The invention discloses an efficient medical
image segmentation method considering
global modeling and local enhancement, and relates to the technical field of
image segmentation. According to the method, adaptive space shift operation is executed in different directions through the AS-MLP module, the long-range dependence modeling capability is effectively enhanced, and the recognition performance of a complex structure focus is improved; the channel and space double attention mechanism and multi-scale
convolution of the LMCAM module are combined, so that fine-grained
feature extraction is realized, and the segmentation precision of the
lesion boundary and the small-
scale structure is remarkably improved; a lightweight network design is adopted, the calculation complexity is low, the reasoning speed is high, and the method is suitable for resource-limited clinical terminals and real-time diagnosis application; besides, the method has good cross-
modal adaptability, can keep stable and efficient segmentation performance in various
medical imaging modalities such as CT, MRI,
ultrasound and dermatoscope, and has wide application value.