基于投影的X光图像分割区域数量判定

为了在随身行李X光图像中自动地检测和识别低亮度的危险物品,首先需要将原始图像进行分割,以得到各个目标的区域.分割图像既不能过分割,也不能欠分割.本文提出了一种基于投影的X光图像分割区域数量判定方法,通过比较分割图像序列在水平和垂直方向投影的相关程度的变化,确定最佳的图像分割区域数量.和基于统计有效指数的方法相比,该方法综合考虑了图像的统计信息和空间分布信息,不仅所得到的最优分割图像中包含足够的目标信息,便于后续的目标检测和识别,而且算法具有较小的计算量.     

Improved AFEM algorithm for bioluminescence tomography based on dual-mesh alternation strategy

Adaptive finite element method (AFEM) is broadly adopted to recover the internal source in biological tissues. In this letter, a novel dual-mesh alternation strategy (dual-mesh AFEM) is developed for biolumi- nescence tomography. By comprehensively considering the error estimation of the finite element method solution on each mesh, two different adaptive strategies based on the error indicator of the reconstructed source and the photon flux density are used alternately in the process. Combined with the constantly adjusted permissible region in the adaptive process, the new algorithm can achieve a more accurate source location compared with the AFEM in the previous experiments.     

Voxel classification methodology for rapid Monte Carlo simulation of light propagation in complex media

Monte Carlo (MC) method is a statistical method for simulating photon propagation in media in the optical molecular imaging field.However,obtaining an accurate result using the method is quite time-consuming,especially because the boundary of the media is complex.A voxel classification method is proposed to reduce the computation cost.All the voxels generated by dividing the media are classified into three types (outside,boundary,and inside) according to the position of the voxel.The classified information is used to determine the relative position of the photon and the intersection between photon path and media boundary in the MC method.The influencing factors and effectiveness of the proposed method are analyzed and validated by simulation experiments.