To assess a novel cell manipulation technique of tissue engineering with respect to its ability to augment superparamagnetic iron oxide particles （SPIO） labeled mesenchymal stem cells （MSCs） density at a localized...To assess a novel cell manipulation technique of tissue engineering with respect to its ability to augment superparamagnetic iron oxide particles （SPIO） labeled mesenchymal stem cells （MSCs） density at a localized cartilage defect site in an in vitro phantom by applying magnetic force. Meanwhile, non-invasive imaging techniques were use to track SPIO-labeled MSCs by magnetic resonance imaging （MRI）. Human bone marrow MSCs were cultured and labeled with SPIO. Fresh degenerated human osteochondral fragments were obtained during total knee arthroplasty and a cartilage defect was created at the center. Then, the osteochondral fragments were attached to the sidewalls of culture flasks filled with phosphate-buffered saline （PBS） to mimic the human joint cavity. The SPIO-labeled MSCs were injected into the culture flasks in the presence of a 0.57 Tesla （T） magnetic force. Before and 90 min after cell targeting, the specimens underwent T2-weighted turbo spin-echo （SET2WI） sequence of 3.0 T MRI. MRI results were compared with histological findings. Macroscopic observation showed that SPIO-labeled MSCs were steered to the target region of cartilage defect. MRI revealed significant changes in signal intensity （P0.01）. HE staining exibited that a great number of MSCs formed a three-dimensional （3D） cell ＂sheet＂ structure at the chondral defect site. It was concluded that 0.57 T magnetic force permits spatial delivery of magnetically labeled MSCs to the target region in vitro. High-field MRI can serve as an very sensitive non-invasive technique for the visualization of SPIO-labeled MSCs.展开更多
针对金属表面缺陷检测任务中检测目标小、尺度变化大、背景复杂等问题,提出了一种基于RTDETR(real-time detection Transformer)的改进模型——HAS-DETR(high accurancy for small object-DETR)。HAS-DETR通过在骨干网络中引入复合差分...针对金属表面缺陷检测任务中检测目标小、尺度变化大、背景复杂等问题,提出了一种基于RTDETR(real-time detection Transformer)的改进模型——HAS-DETR(high accurancy for small object-DETR)。HAS-DETR通过在骨干网络中引入复合差分卷积,增强对小目标的特征提取能力;构建双重多尺度特征融合模块,有效捕获全局语义信息与细节特征,解决目标尺度变化大的问题;设计全局多尺度注意力机制,替代AIFI(attentionbased intra-scale feature interaction)模块中的多头注意力机制,提高模型在复杂背景和多尺度目标场景中的鲁棒性和精确度。在金属表面缺陷数据集上,HAS-DETR在mAP50和mAP50-95上分别较RT-DETR提升了6.5%和4.5%;在公开ADPPP数据集上,mAP50提升了2%,mAP50-95提升了1.3%。实验结果表明:HAS-DETR在保持较高检测效率的同时,有效提升了在复杂背景中对小目标的检测精度,具有良好的实际应用前景。展开更多
基金supported by a grant from the National Natural Sciences Foundation of China (No. 30870639)
文摘To assess a novel cell manipulation technique of tissue engineering with respect to its ability to augment superparamagnetic iron oxide particles （SPIO） labeled mesenchymal stem cells （MSCs） density at a localized cartilage defect site in an in vitro phantom by applying magnetic force. Meanwhile, non-invasive imaging techniques were use to track SPIO-labeled MSCs by magnetic resonance imaging （MRI）. Human bone marrow MSCs were cultured and labeled with SPIO. Fresh degenerated human osteochondral fragments were obtained during total knee arthroplasty and a cartilage defect was created at the center. Then, the osteochondral fragments were attached to the sidewalls of culture flasks filled with phosphate-buffered saline （PBS） to mimic the human joint cavity. The SPIO-labeled MSCs were injected into the culture flasks in the presence of a 0.57 Tesla （T） magnetic force. Before and 90 min after cell targeting, the specimens underwent T2-weighted turbo spin-echo （SET2WI） sequence of 3.0 T MRI. MRI results were compared with histological findings. Macroscopic observation showed that SPIO-labeled MSCs were steered to the target region of cartilage defect. MRI revealed significant changes in signal intensity （P0.01）. HE staining exibited that a great number of MSCs formed a three-dimensional （3D） cell ＂sheet＂ structure at the chondral defect site. It was concluded that 0.57 T magnetic force permits spatial delivery of magnetically labeled MSCs to the target region in vitro. High-field MRI can serve as an very sensitive non-invasive technique for the visualization of SPIO-labeled MSCs.
文摘印刷电路板(Printed Circuit Board,PCB)缺陷会造成巨额经济损失与安全隐患,传统的检测方法精度和效率都较为低下,现有的深度学习模型在面对复杂背景下的小目标检测时存在明显的不足。文章针对YOLOv10在PCB中的检测性能不足,在主干网络采用SPD-Conv模块替代传统卷积,通过维度重排保留小目标的特征并且降低背景干扰。在颈部网络的C2f模块中嵌入SE注意力机制,构建C2f_SE模块提升特征区分度。文章在北京大学PCB数据集的基础上,通过镜像、旋转等数据增强后将数据集扩展至6930张。实验结果表明,改进模型平均精度均值(mean Average Precision,mAP)达98.1%,较原始YOLOv10提升4.7%,其中鼠咬、毛刺等小目标缺陷检测精度提升明显。该模型为工业场景PCB缺陷检测提供了高效可靠方案。
文摘针对金属表面缺陷检测任务中检测目标小、尺度变化大、背景复杂等问题,提出了一种基于RTDETR(real-time detection Transformer)的改进模型——HAS-DETR(high accurancy for small object-DETR)。HAS-DETR通过在骨干网络中引入复合差分卷积,增强对小目标的特征提取能力;构建双重多尺度特征融合模块,有效捕获全局语义信息与细节特征,解决目标尺度变化大的问题;设计全局多尺度注意力机制,替代AIFI(attentionbased intra-scale feature interaction)模块中的多头注意力机制,提高模型在复杂背景和多尺度目标场景中的鲁棒性和精确度。在金属表面缺陷数据集上,HAS-DETR在mAP50和mAP50-95上分别较RT-DETR提升了6.5%和4.5%;在公开ADPPP数据集上,mAP50提升了2%,mAP50-95提升了1.3%。实验结果表明:HAS-DETR在保持较高检测效率的同时,有效提升了在复杂背景中对小目标的检测精度,具有良好的实际应用前景。
