Clinical pathway management of acute exacerbations of chronic obstructive pulmonary disease based on state machine / 南方医科大学学报

We propose a clinical pathway of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) based on state machine. Clinical event-driven response was utilized to control workflow execution of the AECOPD clinical pathway. By comparison with the traditional clinical pathway management, clinical numerical results showed that the proposed method was better in hospitalization days, average hospitalization expense and aberration rate, and better handled the variability in the AECOPD clinical pathway execution.

Progress in visualization of MR diffusion tensor imaging / 生物医学工程学杂志

MR diffusion tensor imaging (DT-MRI) is a new technology which reflects the direction of molecule diffusion better than traditional diffusion weighted imaging (DWI) does. DT-MRI has great advantages of showing the distribution of white matter fiber path and its spatial structures because the water molecules in brain white matters have the obvious anisotropic diffusion. This paper introduces the basics of diffusion tensor imaging, and reviews the visualization methods used with DT-MRI.

Registration and 3D rendering of serial tissue section images / 生物医学工程学杂志

It is an important morphological research method to reconstruct the 3D imaging from serial section tissue images. Registration of serial images is a key step to 3D reconstruction. Firstly, an introduction to the segmentation-counting registration algorithm is presented, which is based on the joint histogram. After thresholding of the two images to be registered, the criterion function is defined as counting in a specific region of the joint histogram, which greatly speeds up the alignment process. Then, the method is used to conduct the serial tissue image matching task, and lies a solid foundation for 3D rendering. Finally, preliminary surface rendering results are presented.

Image Segmentation Method of Gibbs Random Field Accelerated by GPU / 医疗卫生装备

Objective To propose an improved C-means segment method based on Gibbs random field accelerated by GPU.Methods The parallel computation of pixel shades was used to take the place of the classical point-by-point method of CPU.By this way,the efficiency was higher than merely using the CPU computation.Results The efficiency of computation was improved over 400%.The load of CPU was reduced and the effect of accelerator was obvious.Conclusion The improved C-means segment method based on Gibbs random field accelerated by GPU enhances the clinical application of image segmentation,the computer rate of which is improved distinctly and closely to real time.[Chinese Medical Equipment Journal,2008,29(2):6-9]