智能科学与技术学报2025，Vol.7Issue(2)：221-233,13.DOI:10.11959/j.issn.2096-6652.202520
Axial-FNet:基于模糊卷积结合门控轴向自注意力的皮肤癌图像分割模型
Axial-FNet:skin cancer image segmentation model based on fuzzy convolution combined with gated axial self-attention
摘要
Abstract
The task of skin cancer image segmentation is a key task in the field of medical image processing.The com-monly used segmentation algorithms can't well balance the computational resource requirements of local information and global context information when performing diagnosis.In addition,the problem of fuzzy tumor boundaries and difficulty in correctly identifying segmentation is also an urgent problem to be solved.Aiming at the above problems,a skin cancer image segmentation model Axial-FNet based on fuzzy convolution combined with gated axial self-attention was pro-posed.The model was composed of a gated axial self-attention branch and a fuzzy convolutional neural network branch.At the end of the gated axial self-attention branch,a gated weight controller was set to control the proportion and degree of capturing local information and global context information.The fuzzy learning module was fused into the convolu-tional neural network(CNN)to form a fuzzy neural network branch to extract the local information of the image.The seg-mentation accuracy was improved by the model while reducing the amount of calculation.The performance of the Axial-FNet model was evaluated on the ISIC 2017 dataset,achieving scores of 74.23%,83.05%,and 92.89%for MIoU,F1-score,and accuracy,respectively,as well as 80.91%,88.13%,and 93.10%for the same metrics on the ISIC 2018 dataset.The experimental results show that Axial-FNet has better segmentation accuracy and reliability than other advanced seg-mentation models.关键词
图像分割/模糊学习/门控轴向自注意力/门控机制/卷积神经网络Key words
image segmentation/fuzzy learning/gated axial self-attention/gating mechanism/convolutional neural net-work分类
信息技术与安全科学引用本文复制引用
姜舒,陈琨,丁卫平,周天奕,朱越..Axial-FNet:基于模糊卷积结合门控轴向自注意力的皮肤癌图像分割模型[J].智能科学与技术学报,2025,7(2):221-233,13.基金项目
国家重点研发计划项目(No.2024YFE0202700) （No.2024YFE0202700）
国家自然科学基金项目(No.62406153) （No.62406153）
国家级大学生创新创业训练计划项目(No.202410304067Z) （No.202410304067Z）
江苏省自然科学基金项目(No.20231337) （No.20231337）
江苏省高等学校自然科学研究面上项目(No.23KJB520031,No.24KJB520032) The National Key R&D Plan of China(No.2024YFE0202700),The National Natural Science Foundation of China(No.62406153),The National College Students'Innovation and Entrepreneurship Training Program Project(No.202410304067Z),The Natural Science Foundation of Jiangsu Province(No.BK20231337),The General Program of the Natural Sci-ence Research of Higher Education of Jiangsu Province(No.23KJB520031,No.24KJB520032) （No.23KJB520031,No.24KJB520032）
