一种辅助新型冠状病毒肺炎检测的肺实质分割算法

新型冠状病毒肺炎给人类健康及社会经济造成了巨大的负面影响,而X光胸片中的肺实质提取成为新型冠状病毒肺炎诊断过程中的关键环节。在U-Net的基础上,提出一种结合编解码模式的肺实质分割算法。应用特征融合思想,构建A形特征融合模块,充分学习深层特征的语义信息。引入注意力机制,在深层卷积神经网络中加入密集空洞卷积模块和残差多核池化模块,扩大卷积感受野并提取上下文特征信息。通过改进可变形卷积和分割损失函数,提升网络模型的泛化能力和鲁棒性。实验结果表明,该算法的分割准确度、Dice系数、敏感度、Jaccard指数分别为98.16%、98.32%、98.13%、98.54%,能够实现X光胸片中肺实质部位的有效分割。     

一种改进的交互式CT胸部图像肺实质分割方法

提出一种交互式的肺实质分割算法,该算法充分利用序列CT图像相邻层中肺实质轮廓变化缓慢的特点,结合且改进了Live-Wire模型、Snake模型以及轮廓插值方法.并辅以操作人员的专业知识.首先人工的在序列CT图像中选取肺实质的关键层,然后通过Live-Wire模型交互式的勾勒其轮廓,再进行轮廓插值得到其他层肺实质的初始轮廓,最后通过Snake模型演化得到所有层的肺实质准确分割结果,并加以手工修正.实验结果表明,该算法能快速准确的从序列CT图像中分割出肺实质.     

Semi-automated measurement of true chord length distributions and moments by video microscopy and image analysis

The distribution of the lengths of airspace chords in pulmonary parenchyma characterizes many architectural features of the alveoli and alveolar ducts. Laborious to obtain manually, the distributions and density functions may be acquired semi-automatically by video microscopy, digitization and image processing. The accuracy of the estimation is influenced by the microscopical methods and also by the techniques used (i) to convert the digitized grey-scale picture to a two-valued image, (ii) to collect the chord lengths and (iii) to compensate for finite field widths. The last problem arises because some chords are completely visible within a field while others are only partially seen, since one of the two air-tissue boundaries lies outside the field of view. This error systematically biases the observed distribution. This paper contains solutions to hardware, software and analytic problems encountered while developing the capability to measure airspace chord length density functions semi-automatically. Formulas for estimating the true chord length density function from samples of observed chord lengths are presented. Also given are formulas for the estimation of the first and second moments of the true chord length distribution from the means of observed chord lengths. These techniques of image preparation and analysis should be suitable for characterizing particle, grain or cell size distributions, especially where many profiles fall partially outside the field of view.     

基于遗传算法的胸部CT图像肺组织分割

肺组织分割是肺结节检测、肺功能定量分析、三维重建与可视化计算等胸部CT图像分析处理的基础。该文采用了一种基于遗传算法的边缘检测方法直接分割原始胸部CT图像的肺组织，利用遗传算法的全局寻优能力，以最大类间方差为适应度函数自动搜索最佳边缘检测阈值，并结合形态学处理提取肺组织边缘以实现肺组织分割。实验结果表明，该方法能简化分割处理，且分割效果较好，有不错的应用前景。     

Cellular automata and integrodifferential equation models for cell renewal in mosaic tissues

Mosaic tissues are composed of two or more genetically distinct cell types. They occur naturally, and are also a useful experimental method for exploring tissue growth and maintenance. By marking the different cell types, one can study the patterns formed by proliferation, renewal and migration. Here, we present mathematical modelling suggesting that small changes in the type of interaction that cells have with their local cellular environment can lead to very different outcomes for the composition of mosaics. In cell renewal, proliferation of each cell type may depend linearly or nonlinearly on the local proportion of cells of that type, and these two possibilities produce very different patterns. We study two variations of a cellular automaton model based on simple rules for renewal. We then propose an integrodifferential equation model, and again consider two different forms of cellular interaction. The results of the continuous and cellular automata models are qualitatively the same, and we observe that changes in local environment interaction affect the dynamics for both. Furthermore, we demonstrate that the models reproduce some of the patterns seen in actual mosaic tissues. In particular, our results suggest that the differing patterns seen in organ parenchymas may be driven purely by the process of cell replacement under different interaction scenarios.     

一种CT图像的肺实质分割方法

为了实现计算机辅助诊断,解决自动化CT图像处理的问题,文中提出一种肺实质分割的算法.采用求直方图峰值间极小值的方法获取最优阈值,实现图像分割;在此基础上,采用空间滤波以及连通域标记法去除干扰得到肺实质区域.结果表明该方法能实现肺实质分割,解决了肺结节检测的预处理问题.     

慈竹薄壁组织的部分去除对化机浆制浆、漂白性能的影响

采用螺旋挤压法破坏竹片组织结构,并筛除分离部分薄壁组织,选用不同的化学预浸渍方法进行浸渍软化,对制得的不同化学机械浆（CMP）进行过氧化氢漂白对比试验。结果表明：螺旋挤压法去除11.4%薄壁组织后,竹丝化学组成与原竹片相比差异十分明显,其灰分质量分数降低了38.6%,纤维素质量分数增加了4.71%,但螺旋挤压对竹纤维没有造成明显的损伤;碱性过氧化氢（AP）预浸渍可以显著降低磨浆电耗,在加拿大游离度300 mL时,该方法比烧碱（AA）法节电18.0%,并且其化机浆的结合强度较高;AA法浆料的松厚度最高、强度较差;碱性亚硫酸钠（AS）法化机浆的松厚度和强度性能介于AP和AA之间;在H₂O₂用量为8%的漂白条件下,AP、AS和AA预浸渍法的最佳碱用量分别为4.5%、4.5%和3.5%,同时AP预浸渍可以改善漂白效率,漂后浆白度可达56.8%（ISO）,而AA预浸渍化机浆漂白浆白度仅为49.9%（ISO）。     

Distribution of Living Ray Parenchyma Cells and Major Bioactive Compounds During the Heartwood Formation of Taiwania cryptomerioides Hayata

The heartwood of Taiwania (Taiwania cryptomerioides Hayata) has the excellent decay resistance and fascinating color qualities due to the accumulation of bioactive compounds. However, limited information was addressed to the heartwood formation of this species. In this study, we established the distribution of the living ray parenchyma cells and profiled the major bioactive compounds across and along the Taiwania stem. The ray parenchyma cells would die within 1–2 annual rings of the transition zone, which occurs around 8–13 annual rings counted from the cambium. The gradual loss of the starch grains accompanied with the deposition of the colored materials into the cell lumens started from the outer transition zone. The radial distribution of the extractive contents and its signature bioactive compounds across Taiwania stems gradually increased from the transition zone toward the heartwood tissues. The aforementioned properties did not show specific trends along the vertical direction of the Taiwania stems.     

基于CT图像的肺实质分割技术研究

基于CT图像的肺实质分割不仅仅是后续图像处理最基础和最重要的技术,而且是一个典型的亟待解决的问题。基于CT图像的精确的肺实质分割是数学分析、计算机辅助分析和治疗的前提。本文明确了肺实质分割的概念及本质,以及肺实质分割在临床治疗中的重大意义。重点介绍了阈值法、区域生长法、主动轮廓模型和遗传算法,分析了它们的本质以及优缺点,并且列举大量实例说明。最后指出了基于CT图像的肺实质分割方法的发展趋势与面临的挑战。