测试科学与仪器2025，Vol.16Issue(3)：359-370,12.DOI:10.62756/jmsi.1674-8042.2025035
融合局部多尺度特征编码器的SAM医学图像分割模型
A medical image segmentation model based on SAM with an integrated local multi-scale feature encoder
摘要
Abstract
Despite its remarkable performance on natural images,the segment anything model(SAM)lacks domain-specific information in medical imaging.and faces the challenge of losing local multi-scale information in the encoding phase.This paper presents a medical image segmentation model based on SAM with a local multi-scale feature encoder(LMSFE-SAM)to address the issues above.Firstly,based on the SAM,a local multi-scale feature encoder is introduced to improve the representation of features within local receptive field,thereby supplying the Vision Transformer(ViT)branch in SAM with enriched local multi-scale contextual information.At the same time,a multiaxial Hadamard product module(MHPM)is incorporated into the local multi-scale feature encoder in a lightweight manner to reduce the quadratic complexity and noise interference.Subsequently,a cross-branch balancing adapter is designed to balance the local and global information between the local multi-scale feature encoder and the ViT encoder in SAM.Finally,to obtain smaller input image size and to mitigate overlapping in patch embeddings,the size of the input image is reduced from 1 024×1 024 pixels to 256×256 pixels,and a multidimensional information adaptation component is developed,which includes feature adapters,position adapters,and channel-spatial adapters.This component effectively integrates the information from small-sized medical images into SAM,enhancing its suitability for clinical deployment.The proposed model demonstrates an average enhancement ranging from 0.038 7 to 0.319 1 across six objective evaluation metrics on BUSI,DDTI,and TN3K datasets compared to eight other representative image segmentation models.This significantly enhances the performance of the SAM on medical images,providing clinicians with a powerful tool in clinical diagnosis.关键词
分割一切模型/医学图像分割/编码器/解码器/多轴Hadamard积模块/跨分支平衡适配器Key words
segment anything model(SAM)/medical image segmentation/encoder/decoder/multiaxial Hadamard product module(MHPM)/cross-branch balancing adapter引用本文复制引用
邸敬,朱云龙,梁婵..融合局部多尺度特征编码器的SAM医学图像分割模型[J].测试科学与仪器,2025,16(3):359-370,12.基金项目
This work was supported by Natural Science Foundation Programme of Gansu Province(No.24JRRA231),National Natural Science Foundation of China(No.62061023),and Gansu Provincial Science and Technology Plan Key Research and Development Program Project(No.24YFFA024). （No.24JRRA231）
