Background: Rheumatoid arthritis is a form of autoimmune disease characterized by synovitis that can ultimately cause joint deformities and impaired functioning. The cartilage destruction is one of the most important ...Background: Rheumatoid arthritis is a form of autoimmune disease characterized by synovitis that can ultimately cause joint deformities and impaired functioning. The cartilage destruction is one of the most important indicators for diagnosis and treatment of rheumatoid arthritis, and it is radiographically manifested as joint space narrowing. Issue: In the literature, the joint space narrowing progression between a baseline and its follow-up finger joint images can be quantified by using image registration algorithm. We found that the inconsistencies of joint angles may lead to characteristic mismatches and thus severely affect the accuracy of joint space narrowing quantifications. Methods: In this work, we introduce a rotation invariant phase only correlation in joint space narrowing quantification for the joint angle correction. Further, we propose a confidence index to quantify the quantification reliability of phase only correlation based on phase dispersion in phase difference spectrum. Conclusion: In our clinical experiments, the proposed quantification method can effectively overcome and manage the mismatch due to the inconsistency of joint angles. Additionally, the confidence index shows a high consistency with the joint space narrowing progression examinations manually done by a trained radiologist and one radiological technologist.展开更多
瞄准制衡强敌“马赛克战”“决策中心战”等新技术驱动的作战概念及威胁挑战,聚焦未来跨域联合作战指挥控制(command and control,C2)全流程决策需求,遵循平行智能理论框架,提出了基于筹划-准备-执行-评估(planning-readiness-execution...瞄准制衡强敌“马赛克战”“决策中心战”等新技术驱动的作战概念及威胁挑战,聚焦未来跨域联合作战指挥控制(command and control,C2)全流程决策需求,遵循平行智能理论框架,提出了基于筹划-准备-执行-评估(planning-readiness-execution-assessment,PREA)环与观察-判断-决策-行动(observe-orient-decide-act,OODA)环的平行指挥控制与管理(command&control and management,C2M)新范式,以期实现智能机器辅助指挥员作战全流程的分层次、个性化决策支持,减轻指挥员认知负担、降低决策复杂度,实现机器对指挥员“人脑”的智能扩展与增强,为塑造全局决策优势提供牵引和支撑。展开更多
文摘Background: Rheumatoid arthritis is a form of autoimmune disease characterized by synovitis that can ultimately cause joint deformities and impaired functioning. The cartilage destruction is one of the most important indicators for diagnosis and treatment of rheumatoid arthritis, and it is radiographically manifested as joint space narrowing. Issue: In the literature, the joint space narrowing progression between a baseline and its follow-up finger joint images can be quantified by using image registration algorithm. We found that the inconsistencies of joint angles may lead to characteristic mismatches and thus severely affect the accuracy of joint space narrowing quantifications. Methods: In this work, we introduce a rotation invariant phase only correlation in joint space narrowing quantification for the joint angle correction. Further, we propose a confidence index to quantify the quantification reliability of phase only correlation based on phase dispersion in phase difference spectrum. Conclusion: In our clinical experiments, the proposed quantification method can effectively overcome and manage the mismatch due to the inconsistency of joint angles. Additionally, the confidence index shows a high consistency with the joint space narrowing progression examinations manually done by a trained radiologist and one radiological technologist.
文摘针对车载雷达多参数联合超分辨计算复杂度高、无法快速实现参数估计的问题,提出了基于频域波束降维的多参数联合超分辨算法。所提算法通过快速傅里叶变换(fast Fourier transform,FFT)将空时多参数域联合数据变换到频域,处理感兴趣区域的多维频域数据,完成空时波束空间降维和基于频域数据的多参数联合超分辨,实现目标信息的快速联合估计。推导了频域子空间正交性及频域波束降维超分辨算法理论。仿真研究了算法的分辨率和估计性能与信噪比的关系。仿真结果表明,所提算法的精度和分辨率远超传统FFT算法,相对于传统多重信号分类(multiple signal classification,MUSIC)算法,所提算法计算量大幅降低。
文摘瞄准制衡强敌“马赛克战”“决策中心战”等新技术驱动的作战概念及威胁挑战,聚焦未来跨域联合作战指挥控制(command and control,C2)全流程决策需求,遵循平行智能理论框架,提出了基于筹划-准备-执行-评估(planning-readiness-execution-assessment,PREA)环与观察-判断-决策-行动(observe-orient-decide-act,OODA)环的平行指挥控制与管理(command&control and management,C2M)新范式,以期实现智能机器辅助指挥员作战全流程的分层次、个性化决策支持,减轻指挥员认知负担、降低决策复杂度,实现机器对指挥员“人脑”的智能扩展与增强,为塑造全局决策优势提供牵引和支撑。
文摘“任务伙伴环境”(mission partner environment,MPE)是美国防部与任务伙伴共同开展军事任务指挥控制与信息共享的作战框架。研究了美军MPE概念内涵、发展背景,梳理了MPE的类型与支持的行动级别,全面分析了MPE组成架构;重点研究了MPE的核心——多国信息共享(multinational information sharing,MNIS)体系,分析了MNIS的主要组成部分——虚拟数据中心、联合企业区域信息交换系统、联军联邦作战实验室网络、共用任务网络传输系统、“飞马”系统和所有伙伴接入网的功能与发展现状;介绍了MPE的最新发展并分析了MPE从以网络为中心向以数据为中心发展的主要趋势。