基于密集多尺度特征和双注意力模块的皮肤病变分割  

Skin Lesion Segmentation Based on Dense Multi-Scale Features and Dual Attention Module

作　　者：费承 罗健旭[1] FEI Cheng;LUO Jianxu(School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China)

机构地区：[1]华东理工大学信息科学与工程学院,上海200237

出　　处：《华东理工大学学报（自然科学版）》2024年第1期97-105,共9页Journal of East China University of Science and Technology

基　　金：上海市科技创新行动计划(19511121203)。

摘　　要：针对皮肤病变分割任务中病变区域大小不一、形状各异、内部像素差异大、边界模糊、周围存在气泡等问题,提出了一种基于密集多尺度特征和双注意力模块的U型分割网络DDAnet。该网络中的DenseASPP模块通过密集连接多个空洞卷积层来获取丰富的多尺度信息,同时由通道注意力模块(CAM)和位置注意力模块(PAM)构成的双注意力模块通过编码全局上下文信息,在通道和位置上对特征图进行重新配准,实现对相关特征的强调和对无关特征的抑制。两个模块并行连接、共同作用以提高分割精度。在ISIC2018数据集上,DDAnet的准确率(Acc)、Jaccard相似系数(JI)、Dice系数(DC)、敏感度(Sen)和特异性(Spec)指标值分别为96.75%、85.00%、91.36%、91.82%和97.42%,分割结果优于其他的分割网络,并且对于极具挑战的病例,DDAnet仍然能够产生准确、可靠的分割结果,说明其具备在临床诊断中辅助医生进行皮肤病变分割的潜力。Aiming at the problems of varying sizes,shapes,internal pixel differences,blurry boundaries,and presence of bubbles in skin lesion segmentation,a U-shaped segmentation network,DDAnet,based on dense multi-scale features and dual attention module is proposed.The DenseASPP module in this network obtains rich multi-scale information by densely connecting multiple atrous convolution layers.Meanwhile,the dual attention module composed of CAM and PAM encodes global contextual information to re-register feature maps on channels and positions,achieving emphasis on relevant features and suppression of irrelevant features.These two modules are connected in parallel and work together to improve segmentation performance.On the ISIC2018 dataset,the Acc,JI,DC,Sen and Spec index values of DDAnet are 96.75%,85.00%,91.36%,91.82%,and 97.42%,respectively.The segmentation results are better than those of other segmentation networks,and for extremely challenging cases,DDAnet can still produce accurate and reliable segmentation results,indicating its potential to assist doctors in skin lesion segmentation in clinical diagnosis.

关 键 词：皮肤病变分割 DenseASPP模块 CAM PAM 双注意力模块 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]