Research on Segmentation and 3D Reconstruction of human eyes tissue and OCT images

虚拟器官的建模和仿真是当前国际上生物医学工程领域研究的前沿课题。眼睛作为人观察客观事物的视觉器官，是人体最重要的器官之一，对它的建模和仿真具有很高的科学意义和应用价值。随着数字技术进入生物医学领域，医学图像处理技术越来越受到研究工作者的关注和探究。通过医学图像处理可以帮助医师对疾病的诊断，进而指导疾病治疗和预后判断，甚至病因分析等。 本文所研究的主要内容是与眼睛有关的医学图像处理，包括：人眼组织切片和放射状光学相干层析(OCT)视盘两类图像序列的图像分割以及OCT视盘图像的配准、中间插值和三维重建。 根据人眼组织切片序列和取自于活体的放射状OCT眼底视盘图像序列特点，本文分别采用合适的算法...The modeling and simulation of virtual organ is one of the frontier research areas. As an eyespot to observe objective things, eye is one of the most important organs of human. Modeling and simulation of eyes has very high value and application of scientific significance. With digital technology into the field of biomedicine, medical image processing is receiving increasing attention of researcher...学位：工学硕士院系专业：信息科学与技术学院计算机科学系_计算机应用技术学号：2302006115246

加入时变溢价的利率期限结构研究

本文在理性预期假说的基础上,利用上海银行间同业拆借利率(SHIbOr)长短期利率数据,对加入时变风险溢价的利率期限结构进行了实证研究,结果表明:理性预期假说可以解释我国利率市场的预测作用,风险溢价因子为常数时的利率期限结构模型不能解释实际利率数据,而加入经期限修正的风险溢价因子后,利率期限结构模型能够解释长短期利率的预期理论

中药沐足结合护理干预治疗护理人员下肢静脉曲张的效果观察

目的探讨中药沐足结合护理干预在下肢静脉曲张护士中的应用效果。方法选取某三甲综合性医院患有下肢静脉曲张的临床护士60例为研究对象,应用随机数字表法分为两组,各30例。两组研究对象均行基础护理,对照组采用医用的循序减压弹力袜进行治疗,观察组实施中药沐足结合护理干预措施。2个月后比较两组患者疗效。结果观察组研究对象静脉曲张恢复总有效率高于对照组,观察组研究对象经过3个疗程的治疗,痊愈12例,显效l3例,有效4例;对照组分别为痊愈5例,显效8例,有效9例;观察组、对照组临床治愈率和总有效率分别为40.00%、96.67%和16.67%、73.33%。差异有统计学意义(P<0.05)。结论中药沐足结合护理干预可以改善下肢静脉曲张的临床症状。福建中医药大学2016年临床专项校管课题(XB2016085

Cornea Segmentation in Human Eye Tissue Slice Images Based on BP Neural Network

角膜是人眼的一个关键部分,了解角膜的精细结构具有十分重要的意义.本文提出了一种基于BP(Back-propa-gation)网络的,针对组织切片图像序列提取角膜局部信息的新方法.首先对切片序列进行预处理,截取包含角膜信息的原1/2图像,其次选取预处理过的图像序列中角膜颜色差异的若干图片做训练样本,以人工分割后的图像作为导师信号,通过分析选取6个图像特征作为输入向量,对三层BP神经网络进行训练.训练完成后,采用该网络对图像序列进行分割,最后对分割图像进行后处理包括区域分割、孔洞填充及恢复图像大小.实验结果表明,该方法能够获得较好的图像序列分割效果,为角膜精细形态模型的建立及其后续研究打下基础,同时也为眼内其他重要结构的分割提供一种参考方法.Cornea is one of the most important parts of human body′s eyes.According to the particular obtainment of the human eyes tissue images,in this paper,a method to extract cornea′s local information based on back-propagation(BP) neural network is proposed.First,we capture half of the images including cornea information.Then several images with different cornea colors are chosen as training samples.Manual segmentation images of training samples are used as teacher signals.The network′s input vectors are 6 image features.We can train the BP neutral network with 3 layers and capture the segmented images.Finally,we get the exactly cornea information by region growing with the segmented images and filling holes of images.This method is turned out to get expected purpose and operate little subjective.It is a reference method to segment the other parts of eyes of these tissue slice images,and also is a basis for the research of modal model of cornea.国家自然科学基金(60371012,60601025,30770561);; 卫生部科学研究基金-福建省卫生教育联合攻关计划项目(WKJ2005-2-001)资

Cornea Segmentation in Human Eye Tissue Slice Images Based on BP Neural Network

中文摘要: 角膜是人眼的一个关键部分 ,了解角膜的精细结构具有十分重要的意义.本文提出了一种基于 BP (Back-propa-gation)网络的 ,针对组织切片图像序列提取角膜局部信息的新方法.首先对切片序列进行预处理 ,截取包含角膜信息的原 1/ 2 图像 ,其次选取预处理过的图像序列中角膜颜色差异的若干图片做训练样本 ,以人工分割后的图像作为导师信号 ,通过分析选取 6 个图像特征作为输入向量 ,对三层BP神经网络进行训练.训练完成后 ,采用该网络对图像序列进行分割 ,最后对分割图像进行后处理包括区域分割、 孔洞填充及恢复图像大小.实验结果表明 ,该方法能够获得较好的图像序列分割效果 ,为角膜精细形态模型的建立及其后续研究打下基础 ,同时也为眼内其他重要结构的分割提供一种参考方法. 英文摘要：Cornea is one of the most importantparts of human body′s eyes. According to the particular obtainment of the human eyes tissue images ,in this paper ,a method to extract cornea′s local information based on back-propagation (BP) neural network is proposed. First ,we capture half of the images including cornea information. Then several images with different cornea colors are chosen as training samples. Manual segmentation images of training samples are used as teacher signals. The network′s input vectors are 6 image features. We can train the BP neutral network with 3 layers and capture the segmented images. Finally ,we get the exactly cornea information by region growing with the segmented images and filling holes of images. This method is turned out to get expected purpose and operate little subjective. It is a reference method to segment the other parts of eyes of these tissue slice images ,and also is a basis for the research of modal model of cornea.国家自然科学基金(60371012 ,60601025 ,30770561) ,卫生部科学研究基金2福建省卫生教育联合攻关计划项目(WKJ2005222001)资

Amino acid composition and its biogeochemistry implications of surface sediments in coastal areas of China

1 引言 氨基酸是大多数生物体有机氮和有机碳的主要组分,也是近代沿海海洋沉积物有机质的重要组成部分~([1])

Segmentation Algorithm of CT Image Liver Parenchyma Based on BP Network

提出一种基于BP网络分割CT图像序列中肝实质的方法。首先选取训练样本,提取样本图像中肝脏的纹理特征,作为输入向量,以对训练样本手工分割的结果作为导师信号,对BP神经网络进行训练,再用训练好的网络对CT图像序列中的肝实质进行分割,最后对分割后的结果进行三维区域生长及孔洞填充处理。实验结果表明:该方法能够有效的对肝脏纹理特征明显的CT图像序列进行分割,可用于CT图像序列的自动分割。It puts forward a method to segment liver parenchyma in CT image sequence based on BP network. Firstly, select the training sample, extract the texture features of liver in sample image as input vector, take the result of manual segmentation on training sample as teacher signal to train BP neutral network, and then make segmentation on liver parenchyma in CT image sequence by trained network, and finally, make 3-D domain growth and hole filling and treat-ment for the result after segmentation. The experimental result shows that this method can effectively segment CT image sequence with obvious liver texture features, which can be applied to the automatic segmentation of CT image sequence.国家自然科学基金(30770561,60701022);; 卫生部科学研究基金—福建省卫生教育联合攻关计划资助项目(WKJ2005-2-001)~

Multi-species particle swamis optimization based on orthogonal learning and its application for optimal design of a butterfly-shaped patch antenna

A new multi-species particle swarm optimization with a two-level hierarchical topology and the orthogonal learning strategy (OMSPSO) is proposed, which enhances the global search ability of particles and increases their convergence rates. The numerical results on 10 benchmark functions demonstrated the effectiveness of our proposed algorithm. Then, the proposed algorithm is presented to design a butterfly-shaped microstrip patch antenna. Combined with the HFSS solver, a butterfly-shaped patch antenna with a bandwidth of about 40.1% is designed by using the proposed OMSPSO. The return loss of the butterfly-shaped antenna is greater than 10 dB between 4.15 and 6.36 GHz. The antenna can serve simultaneously for the high-speed wireless computer networks (5.15-5.35 GHz) and the RFID systems (5.8 GHz)

Artificial Bee Colony Algorithm Based on K-Means Clustering for Droplet Property Optimization

The major challenge in printable electronics fabrication is to effectively and accurately control a drop-on-demand (DoD) inkjet printhead for high printing quality. In this paper, a prediction model based on Lumped Element Modeling (LEM) is proposed to search the parameters of driving waveform for obtaining the desired droplet properties. Although the evolution algorithms are helpful to solve this problem, the classical evolution algorithms may get trapped into local optimal due to the inefficiency of local search. To overcome it, we present an improved artificial bee colony algorithm based on K-means clustering (KCABC), which enhances the population diversity by dynamically clustering and increases the convergence rates by the modification of information communication in the employed bees&rsquo; phase. Combined with KCABC, the prediction model is applied to optimize the droplet volume and velocity of nano-silver ink for high printing quality. Experimental results demonstrate the proposed prediction model with KCABC plays a good performance in terms of efficiency and accuracy of searching the appropriate combination of waveform parameters for printable electronics fabrication