基于X射线断层成像的逆向工程中轮廓序列分割算法的原理及实现

为了实现基于X射线断层成像(CT)的逆向工程中具有参数识别的三维图像重构, 提出了一种分割轮廓序列的新算法. 首先通过一定角度的射线法来得到轮廓间的嵌套关系,然后采用扫描一次关系矩阵生成轮廓树的方法实现层内轮廓定位, 最后运用轮廓间定量、定性的属性判定来完成层间的轮廓匹配. 通过实例, 本文提供的算法可以准确、快速地分割CT零件中的轮廓序列.     

An Interpretation Architecture for Deep Learning Models with the Application of COVID-19 Diagnosis

The Coronavirus disease 2019 (COVID-19) has become one of the threats to the world. Computed tomography (CT) is an informative tool for the diagnosis of COVID-19 patients. Many deep learning approaches on CT images have been proposed and brought promising performance. However, due to the high complexity and non-transparency of deep models, the explanation of the diagnosis process is challenging, making it hard to evaluate whether such approaches are reliable. In this paper, we propose a visual interpretation architecture for the explanation of the deep learning models and apply the architecture in COVID-19 diagnosis. Our architecture designs a comprehensive interpretation about the deep model from different perspectives, including the training trends, diagnostic performance, learned features, feature extractors, the hidden layers, the support regions for diagnostic decision, and etc. With the interpretation architecture, researchers can make a comparison and explanation about the classification performance, gain insight into what the deep model learned from images, and obtain the supports for diagnostic decisions. Our deep model achieves the diagnostic result of 94.75%, 93.22%, 96.69%, 97.27%, and 91.88% in the criteria of accuracy, sensitivity, specificity, positive predictive value, and negative predictive value, which are 8.30%, 4.32%, 13.33%, 10.25%, and 6.19% higher than that of the compared traditional methods. The visualized features in 2-D and 3-D spaces provide the reasons for the superiority of our deep model. Our interpretation architecture would allow researchers to understand more about how and why deep models work, and can be used as interpretation solutions for any deep learning models based on convolutional neural network. It can also help deep learning methods to take a step forward in the clinical COVID-19 diagnosis field.     

MCNP Dose Calculations in a CT Phantom for Therapeutic External Photon Beam

In this paper, we have addressed the problem of the radiation transport with the Monte Carlo N particle(MCNP) code. This is a general purpose Monte Carlo tool designed to transport neutron, photon and electron in three dimensional geometries. To examine the performance of MCNP5 code in the field of external radiotherapy, we performed the modeling of an Electron Density phantom (EDP) irradiated by photons from 60Co source. The model was used to calculate the Percent Depth Dose (PDD) at different depths in an EDP. One field size for PDD has been examined. A 60Co photons source placed at 80 cm source to surface distance (SSD). The results of calculations were compared to TPS data obtained at National Institute of Oncology of Rabat.     

螺旋锥束CT中两种解析重建算法的研究

 研究了锥束螺旋Katsevich和FDK重建算法,并对这两种算法进行比较。实验结果表明：当投影数据没有噪声的时候,FDK算法和Katsevich算法均能取得较好的效果,当对实际物体进行重建的时候,投影数据含有噪声, Katsevich算法需要对投影数据求导,而它对投影数据的噪声较敏感,重建质量有所下降。     

岩石加卸荷破坏细观机理CT实时分析

利用与CT(computerizedtomography)机配套的专用岩石三轴加载试验设备 ,采用CT实时试验的手段对连续加载试验条件下和卸围压应力作用下砂岩破坏细观机理进行了对比研究。结果表明 ,岩石的卸荷损伤演化破坏具有突发性 ,卸围压破坏导致的扩容比连续加载破坏时大.     

单轴条件下砂岩三维破裂过程的CT观测

岩石破裂过程研究一直是岩石力学专家关注的重要问题。本文采用特制的三轴压力仪与医用西门子SOMATOM -plusCT扫描仪结合 ,对砂岩进行了室内单轴压缩试验。通过对砂岩的CT图像和密度损伤增量与应力关系曲线分析 ,结果显示 ,砂岩的破裂演化过程可分为初始损伤的压密、裂纹出现—扩展、裂纹归并—分岔、裂纹重分岔—扩展以及裂纹惯通—宏观破坏等五个阶段。在初始损伤的压密阶段 ,砂岩的密度损伤增量为正值 ,速率也为正 ;在裂纹出现—扩展阶段 ,砂岩出现局部密度损伤增量减小 ,并随应力增加而由正值转为负值 ,速率也由正变负 ;在裂纹归并—分岔阶段 ,砂岩的密度损伤增量全为负值 ,速率也变快 ;在裂纹重分岔—扩展阶段 ,砂岩的密度损伤增量继续变负 ,但速率变慢 ;在裂纹惯通—宏观破坏阶段 ,砂岩的密度损伤增量继续变负 ,速率变的更快。     

Synthesis and Characterization of a Biologically Active Lanthanum(III)–Catechin Complex and DNA Binding Spectroscopic Studies

A lanthanum(III) complex of catechin has been synthesized and characterized by elemental analysis, molar conductance, UV-Vis spectra, infrared spectra, thermal analysis, and ¹H NMR. The complex behaves as a nonelectrolyte in methanol solvent. The spectral and thermal properties of the complex are examined. A thermogravimetric (TGA) study showed the hydrated nature of the complex. ¹H NMR spectra of the lanthanum and the catechin (CT) ligands measured in CD₃OD-d₄ also show metal ligand coordination. The lanthanum–catechin complex shows bright luminescence in methanol solution. The interaction of the complex with calf thymus DNA has been investigated by absorption and emission spectroscopic measurements. Experimental spectral results suggest CT–DNA binding with catechin complex via an intercalative mode.     

Experimental investigation of liquid chromatography columns by means of computed tomography

The efficiency of packed chromatographic columns was investigated experimentally by means of computed tomography (CT) techniques. The measurements were carried out by monitoring tracer fronts in situ inside the chromatographic columns. The experimental results were fitted using the equilibrium dispersive model (EDM) and varying the so called apparent axial dispersion coefficient. The additivity of the first and second central moments was exploited to estimate column efficiency in different regions of the column. The results showed that the columns under investigation offered a higher column efficiency in the centre compared to the wall region. Furthermore the void fraction in the vicinity of the walls was lower than that in the column core. For this reason the bands were conveyed faster in the central region of the column where the permeability was higher. This result is in good agreement with earlier findings.     

散射光子对60Co集装箱CT检测系统的影响

用蒙特卡罗（EGSnrc）方法模拟计算集装箱（大型客体）CT检测系统60Co光子能谱，讨论和分析了该检测系统的客体散射光子对影像分辨率的影响，为进一步提高集装箱（大型客体）CT检测系统数字成像分辨率提供了理论依据.