MUSCLE：用于多身体部位X射线图像深度模型预训练的多任务自监督持续学习
MUSCLE: Multi-task Self-supervised Continual Learning to Pre-train Deep Models for X-ray Images of Multiple Body Parts
AI总结：
该研究提出多任务自监督持续学习框架MUSCLE，通过聚合多部位X射线数据、结合MoCo表征学习与持续学习策略解决相关问题，在9个真实数据集上验证了其能提升X射线图像分析性能。
摘要：
尽管自监督学习（SSL）算法已被广泛用于深度模型的预训练，但鲜有研究[11]借助SSL预训练模型来改进X射线图像分析的表征学习。本研究中，我们针对多种医学影像任务（如分类、分割），提出了一种名为多任务自监督持续学习（MUSCLE）的新型自监督预训练流程，该流程使用从头部、肺部、骨骼等多个身体部位采集的X射线图像。具体而言，MUSCLE聚合多身体部位采集的X射线图像开展基于MoCo（动量对比）的表征学习，并采用精心设计的持续学习（CL）流程，针对各类X射线分析任务联合进一步预训练骨干网络。MUSCLE中运用了图像预处理、学习率调度和正则化相关的若干策略，以解决多任务/数据集学习存在的数据异质性、过拟合和灾难性遗忘问题。我们使用9个真实世界X射线数据集对MUSCLE进行评估，涉及肺炎分类、骨骼异常分类、肺部分割和肺结核（TB）检测等多种任务。与其他预训练模型[7]的对比验证了概念可行性：自监督多任务/数据集持续预训练能够提升X射线图像分析的性能。
英文摘要：
While self-supervised learning (SSL) algorithms have been widely used to pre-train deep models, few efforts [11] have been done to improve representation learning of X-ray image analysis with SSL pre-trained models. In this work, we study a novel self-supervised pre-training pipeline, namely Multi-task Self-super-vised Continual Learning (MUSCLE), for multiple medical imaging tasks, such as classification and segmentation, using X-ray images collected from multiple body parts, including heads, lungs, and bones. Specifically, MUSCLE aggregates X-rays collected from multiple body parts for MoCo-based representation learning, and adopts a well-designed continual learning (CL) procedure to further pre-train the backbone subject various X-ray analysis tasks jointly. Certain strategies for image pre-processing, learning schedules, and regularization have been used to solve data heterogeneity, overfitting, and catastrophic forgetting problems for multi-task/dataset learning in MUSCLE.We evaluate MUSCLE using 9 real-world X-ray datasets with various tasks, including pneumonia classification, skeletal abnormality classification, lung segmentation, and tuberculosis (TB) detection. Comparisons against other pre-trained models [7] confirm the proof-of-concept that self-supervised multi-task/dataset continual pre-training could boost the performance of X-ray image analysis.
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