| There are more and more AI applications in the medical field,and the medical diagnosis is more and more accurate.The multimodal medical image segmentation is an important application in the medical field.The operation of segmentation is usually done manually by professional doctors.Based on AI technology,the work efficiency of doctors will be improved by the automatic segmentation system.This dissertation is divided into three parts.Firstly,the technology and background of multimodal medical image segmentation are introduced.Secondly,the design and implementation of multimodal medical image segmentation algorithm are analyzed,including the model structure design and training strategy.Through a series of ablation experiments and comparative experiments,the author designs and optimizes the algorithm that can accurately segment the organ region,and compares it with the current network model commonly used.Thirdly,the system design based on the medical segmentation algorithm are described.Compared with the current leading segmentation algorithm and classical segmentation algorithm,the medical image segmentation algorithm proposed in this dissertation is more accurate.The medical assistant diagnosis system including the segmentation algorithm has passed the relevant tests,and can perform auxiliary analysis normally. |
