基于元学习和神经架构搜索的半监督医学图像分割方法OA
Semi-Supervised Medical Image Segmentation Method Based on Meta-Learning and Neural Architecture Search
多数医学图像分割方法主要在相同或者相似医疗数据领域进行训练和评估,意味其需要大量像素级别的标注.但这些模型在领域分布外的数据集上面临挑战,被称为"域偏移"问题.通常使用固定的U形分割架构解决该问题,导致其无法更好地适应特定分割任务.文中提出了一种基于梯度的元学习与神经架构搜索方法,可以根据特定任务调整分割网络以实现良好的性能并且拥有良好的泛化能力.该方法主要使用特定任务进行架构搜索模块来进一步提升分割效果,再使用基于梯度的元学习训练算法提升泛化能…查看全部>>
Most medical image segmentation methods mainly focus on training and evaluating in the same or similar medical data domain,which need lots of pixel-level annotations.However,these models face challenges in out-of-distribution medical data set,which is known as"domain shift"problem.A fixed U-shaped segmentation structure is usually used to solve this problem,resulting in it not being better adapted to specific partition tasks.A gradient-based meta-learning an…查看全部>>
于智洪;李菲菲
上海理工大学 光电信息与计算机工程学院,上海 200093上海理工大学 光电信息与计算机工程学院,上海 200093
计算机与自动化
医学图像分割元学习神经架构搜索域泛化解耦表示半监督学习卷积神经网络深度学习
medical image segmentationmeta-learningneural architecture searchdomain generalizationdisentangle representationssemi-supervised learningconvolutional neural networkdeep learning
《电子科技》 2024 (1)
17-23,7
上海市高校特聘教授(东方学者)岗位计划(ES2015XX)The Program for Professor of Special Appointment(Eastern Scholar)at Shanghai Institutions of Higher Learning(ES2015XX)
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