感兴趣区域在临床医学图像分析中占有重要地位.提出了一种基于单调推进曲线进化的感兴趣区域提取新方法.首先,通过极小化ROI(region of interest)能量函数,推导出区域速度函数项,并与基于边界的速度函数融合,提出融合ROI信息的单调推进S...感兴趣区域在临床医学图像分析中占有重要地位.提出了一种基于单调推进曲线进化的感兴趣区域提取新方法.首先,通过极小化ROI(region of interest)能量函数,推导出区域速度函数项,并与基于边界的速度函数融合,提出融合ROI信息的单调推进Snake模型.ROI信息能够增强曲线深入到对比度低且细窄的区域中的传播能力.其次,提出了多初始化快速推进算法,选择性地种植种子曲线有助于局部区域的生长从而进一步改善分割结果.此外,为提高计算效率,在多尺度空间进行数值求解,其中利用快速解传递方法实现粗一级尺度到细一级尺度解的传递,可以加速收敛.利用医学图像分割实验对该方法进行评估,结果表明:该方法能够快速、精确地提取低对比度和细窄的ROI区域.与现有方法相比,该方法的高效性同时体现在分割结果和计算代价上.展开更多
Path planning for field agricultural robots must satisfy several criteria:establishing feeding routes,maintaining gentle slopes,approaching multiple livestock observation points,ensuring timely environmental monitorin...Path planning for field agricultural robots must satisfy several criteria:establishing feeding routes,maintaining gentle slopes,approaching multiple livestock observation points,ensuring timely environmental monitoring,and achieving high efficiency.The complex terrain of outdoor farming areas poses a challenge.Traditional A*algorithms,which generate only the shortest path,fail to meet these requirements and often produce paths that lack smoothness.Therefore,identifying the most suitable path,rather than merely the shortest one,is essential.This study introduced a path-planning algorithm tailored to field-based livestock farming environments,building upon the traditional A*algorithm.It constructed a digital elevation model,integrated an artificial potential field for evaluating multiple target points,calculated terrain slope,optimized the search neighborhood based on robot traversability,and employed Bézier curve segmentation for path optimization.This method segmented the path into multiple curves by evaluating the slopes of the lines connecting adjacent nodes,ensuring a smoother and more efficient route.The experimental results demonstrate its superiority to traditional A^(*),ensuring paths near multiple target points,significantly reducing the search space,and resulting in over 69.4%faster search speeds.Bézier curve segmentation delivers smoother paths conforming to robot trajectories.展开更多
文摘感兴趣区域在临床医学图像分析中占有重要地位.提出了一种基于单调推进曲线进化的感兴趣区域提取新方法.首先,通过极小化ROI(region of interest)能量函数,推导出区域速度函数项,并与基于边界的速度函数融合,提出融合ROI信息的单调推进Snake模型.ROI信息能够增强曲线深入到对比度低且细窄的区域中的传播能力.其次,提出了多初始化快速推进算法,选择性地种植种子曲线有助于局部区域的生长从而进一步改善分割结果.此外,为提高计算效率,在多尺度空间进行数值求解,其中利用快速解传递方法实现粗一级尺度到细一级尺度解的传递,可以加速收敛.利用医学图像分割实验对该方法进行评估,结果表明:该方法能够快速、精确地提取低对比度和细窄的ROI区域.与现有方法相比,该方法的高效性同时体现在分割结果和计算代价上.
基金supported by the Subject construction projects in specific universities(Grant No.2023B10564003)the Science and Technology Rural Commissioner Project of Guangzhou(Grant No.20212100026).
文摘Path planning for field agricultural robots must satisfy several criteria:establishing feeding routes,maintaining gentle slopes,approaching multiple livestock observation points,ensuring timely environmental monitoring,and achieving high efficiency.The complex terrain of outdoor farming areas poses a challenge.Traditional A*algorithms,which generate only the shortest path,fail to meet these requirements and often produce paths that lack smoothness.Therefore,identifying the most suitable path,rather than merely the shortest one,is essential.This study introduced a path-planning algorithm tailored to field-based livestock farming environments,building upon the traditional A*algorithm.It constructed a digital elevation model,integrated an artificial potential field for evaluating multiple target points,calculated terrain slope,optimized the search neighborhood based on robot traversability,and employed Bézier curve segmentation for path optimization.This method segmented the path into multiple curves by evaluating the slopes of the lines connecting adjacent nodes,ensuring a smoother and more efficient route.The experimental results demonstrate its superiority to traditional A^(*),ensuring paths near multiple target points,significantly reducing the search space,and resulting in over 69.4%faster search speeds.Bézier curve segmentation delivers smoother paths conforming to robot trajectories.
