湖北民族大学学报（自然科学版）2025，Vol.43Issue(3)：346-350,356,6.DOI:10.13501/j.cnki.42-1908/n.2025.09.005
基于动态卷积与Mamba的双分支尘肺病分期模型
Dual-branch Pneumoconiosis Staging Model Based on Dynamic Convolution and Mamba
摘要
Abstract
To address the issues of sparse lesion distribution,variable morphology,and small inter-class differences in pneumoconiosis X-ray chest films,a dual-branch pneumoconiosis staging model based on dynamic convolution and Mamba(DC-Mamba)was proposed.First,the model enhanced the extraction of local features of small fibrotic lesions through the adaptive kernel parameter generation strategy of the dynamic convolution branch.Meanwhile,the global spatial dependencies of multi-regional lesions were captured by leveraging the sequential modeling capability of the Mamba branch.Second,a feature fusion module with dual-path attention collaboration mechanism was designed to integrate local details and global contextual information.The model was validated on 1760 real anonymized patient X-ray chest films.The results showed that the accuracy of DC-Mamba model reached 78.3%,the recall was 79.0%,and the F1 score was 77.6%,all of which were superior to contrast models.DC-Mamba significantly improved the model's understanding of the overall distribution of pulmonary lesions and the detection of subtle lesions,thereby enhancing the early screening and precise staging capacities of pneumoconiosis.关键词
尘肺病分期/X光胸片/动态卷积/Mamba/特征融合/多区域病灶Key words
pneumoconiosis staging/X-ray chest films/dynamic convolution/Mamba/feature fusion/multi-regional lesions分类
信息技术与安全科学引用本文复制引用
王一帆,苏树智,尹欣乐,赵晨琦,杨帆..基于动态卷积与Mamba的双分支尘肺病分期模型[J].湖北民族大学学报（自然科学版）,2025,43(3):346-350,356,6.基金项目
国家自然科学基金项目(52374155) （52374155）
安徽省高等学校自然科学研究项目(2024AH050399) （2024AH050399）
合肥综合性国家科学中心大健康研究院职业医学与健康联合研究中心研究项目(OMH-2023-05 （）
OMH-2023-24) （）
安徽理工大学医学专项培育项目(YZ2023H2A007). （YZ2023H2A007）
