树木病虫害缺陷精准检测方法的综述和展望

我国疆土辽阔,有着丰富的森林资源。近年来,随着外来昆虫的入侵,全国树木病虫害的暴发率逐年上升,对我国生态经济造成了巨大的影响,但是树木病虫害的监测只能在局部地区,因而只能在已经暴发了较严重的病虫害后才能够发现和治理。树木病虫害如在早期未被发现和处理,可能会造成暴发的严重形势,且预防和治理将变得被动,因此,进行树木内部病虫害缺陷精准检测尤为重要。为更早和更加准确预报树木病虫害的发生,需要进行定期的检测和监控。针对早期传统方法如目测法、敲击辩声法和解剖观测法等方法的准确性低、时效性差和易对树木造成不可逆损害等缺点,近些年研究出了新的检测方法,包括指向性好、能量大的超声波检测法,低成本、穿透性强的应力波检测法,以及成像准确、适用于不同环境的电磁波检测法等。不同的检测方法分别有着相对应的成像算法,如走时法、频域分析法和Born近似法等。这些成像算法在分辨率、准确度、精度和计算速度上各有优势。通过对这3种检测方法的发展现状进行总结,了解各类检测方法的优缺点,有助于更好地针对不同情况下的树木病虫害做出精准检测,能够把树木病虫害暴发后的被动治理变成暴发前的主动预防,以提早做出应对方案。     

宝石能谱CT的功能特点及心血管检查的临床应用

宝石能谱CT拥有一系列独特的技术,包括宝石探测器、高压发射器、ASIR重组技术、能谱栅技术等,使其具有低剂量高清成像、能谱成像和动态500排成像特点,实现了全身0.23mm的极限空间分辨率和类MRI的软组织低密度分辨率,为心脏能量成像、斑块性质的鉴别及金属伪影的消除提供了全新有效的手段。其特有的高纯度和高通透性的物理学特性,再加上影像链中采样率的增高,专有的高清算法,使得宝石能谱CT能够在更低的剂量下,获得更为清晰的图像质量,达到目前业内最高的空间分辨率和密度分辨率;同时,其独有的能谱栅成像技术,将CT诊断从形态学带入功能学领域,因此也被称为"显微CT,病理CT,绿色CT",宝石能谱CT代表了目前CT发展的趋势,它用准确的绝对CT值的单能量成像(keV)诊断和基物质成像诊断来取代传统的相对CT值的混合能量(kVp)成像诊断,用多参数CT成像诊断来代替传统的单参数CT成像诊断,而"三同"(同时、同源、同向)的物理基础保证了其能谱成像的准确性,使CT能谱成像真正走入了临床诊断的第一线,从而提高了心血管疾病诊断的准确性和安全性。为CT在心脏疾病的诊断方面开拓了新领域和新方法。     

Advanced high resolution three-dimensional imaging to visualize the cerebral neurovascular network in stroke

As an important method to accurately and timely diagnose stroke and study physiological characteristics and pathological mechanism in it, imaging technology has gone through more than a century of iteration. The interaction of cells densely packed in the brain is three-dimensional (3D), but the flat images brought by traditional visualization methods show only a few cells and ignore connections outside the slices. The increased resolution allows for a more microscopic and underlying view. Today''s intuitive 3D imagings of micron or even nanometer scale are showing its essentiality in stroke. In recent years, 3D imaging technology has gained rapid development. With the overhaul of imaging mediums and the innovation of imaging mode, the resolution has been significantly improved, endowing researchers with the capability of holistic observation of a large volume, real-time monitoring of tiny voxels, and quantitative measurement of spatial parameters. In this review, we will summarize the current methods of high-resolution 3D imaging applied in stroke.     

In vivo molecular and single cell imaging

Molecular imaging is used to improve the disease diagnosis, prognosis, monitoring of treatment in living subjects. Numerous molecular targets have been developed for various cellular and molecular processes in genetic, metabolic, proteomic, and cellular biologic level. Molecular imaging modalities such as Optical Imaging, Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), and Computed Tomography (CT) can be used to visualize anatomic, genetic, biochemical, and physiologic changes in vivo. For in vivo cell imaging, certain cells such as cancer cells, immune cells, stem cells could be labeled by direct and indirect labeling methods to monitor cell migration, cell activity, and cell effects in cell-based therapy. In case of cancer, it could be used to investigate biological processes such as cancer metastasis and to analyze the drug treatment process. In addition, transplanted stem cells and immune cells in cell-based therapy could be visualized and tracked to confirm the fate, activity, and function of cells. In conventional molecular imaging, cells can be monitored in vivo in bulk non-invasively with optical imaging, MRI, PET, and SPECT imaging. However, single cell imaging in vivo has been a great challenge due to an extremely high sensitive detection of single cell. Recently, there has been great attention for in vivo single cell imaging due to the development of single cell study. In vivo single imaging could analyze the survival or death, movement direction, and characteristics of a single cell in live subjects. In this article, we reviewed basic principle of in vivo molecular imaging and introduced recent studies for in vivo single cell imaging based on the concept of in vivo molecular imaging.     

Variability of Microcirculation Detected by Blood Pulsation Imaging

The non-invasive assessment of blood flow is invaluable for the diagnostic and monitoring treatment of numerous vascular and neurological diseases. We developed a non-invasive and non-contact method of blood pulsation imaging capable of visualizing and monitoring of the two-dimensional distribution of two key parameters of peripheral blood flow: the blood pulsation amplitude and blood pulsation phase. The method is based on the photoplethysmographic imaging in the reflection mode. In contrast with previous imaging systems we use new algorithm for data processing which allows two dimensional mapping of blood pulsations in large object''s areas after every cardiac cycle. In our study we carried out the occlusion test of the arm and found (i) the extensive variability of 2D-distribution of blood pulsation amplitude from one cardiac cycle to another, and (ii) existence of the adjacent spots to which the blood is asynchronously supplied. These observations show that the method can be used for studying of the multicomponent regulation of peripheral blood circulation. The proposed technique is technologically simple and cost-effective, which makes it applicable for monitoring the peripheral microcirculation in clinical settings for example, in diagnostics or testing the efficiency of new medicines.     

基于空间频域滤波高动态光学投影层析的斑马鱼三维成像研究

本文提出了一种基于空间频率滤波的多曝光融合的高动态投影层析三维成像方法,实现了活体斑马鱼（17 mm × 4 mm,最大厚度为2.33 mm,最小厚度为0.29 mm）的三维结构成像. 通过相机采用不同曝光时间记录系列吸收图像,将每张图像取变换到频域去除低频后,将各张滤波后叠加并逆傅里叶变换回空域,对变换后的图像进行归一化处理,最终获得高动态图像. 在每个投影角度获得这种高动态吸收投影图像,进行滤波反投影算法重建,获得高动态的整条斑马鱼三维结构信息. 实验成像结果表明,这种空间频率滤波多曝光融合的高动态光学投影层析三维成像研究,可以获得复杂结构更丰富的空间信息,对斑马鱼等模式生物早期胚胎生长发育进程进行监测和定量评估有一定的应用前景.     

A mechanical model to compute elastic modulus of tissues for harmonic motion imaging

Numerous experimental and computational methods have been developed to estimate tissue elasticity. The existing testing techniques are generally classified into in vitro, invasive in vivo and non-invasive in vivo. For each experimental method, a computational scheme is accordingly proposed to calculate mechanical properties of soft biological tissues. Harmonic motion imaging (HMI) is a new technique that performs radio frequency (RF) signal tracking to estimate the localized oscillatory motion resulting from a radiation force produced by focused ultrasound. A mechanical model and computational scheme based on the superposition principle are developed in this paper to estimate the Young's modulus of a tissue mimicking phantom and bovine liver in vitro tissue from the harmonic displacement measured by HMI. The simulation results are verified by two groups of measurement data, and good agreement is shown in each comparison. Furthermore, an inverse function is observed to correlate the elastic modulus of uniform phantoms with amplitude of displacement measured in HMI. The computational scheme is also implemented to estimate 3D elastic modulus of bovine liver in vitro.     

Patient realignment in magnetic resonance imaging of the head: an algorithm using mathematical morphology for feature extraction

To develop a technique for automatic patient realignment in magnetic resonance imaging (MRI), it is essential to extract key features automatically from the various slices of the head as accurately as possible. Such features include the brain, the brain stem, the pons, the corpus callosum and the cerebellum. A feature extraction algorithm has been developed which is based on thresholding a region to a common grey level and then applying mathematical morphology to produce a binary regular region. In addition, a region-filling algorithm has been developed to obtain the complete feature. The scans derived from the T1 spin-lattice relaxation time, which are the fastest of the MRI scans, are used in patient realignment to provide highly textured images. These are difficult to segment using conventional thresholding or edge enhancement techniques due to their ‘grainy’ appearance, which makes it difficult to isolate key features from the other components found in the slice. We have developed a method for the accurate extraction of the corpus callosum, the cerebellum and the brain area in a sagittal scan of the head. This is carried out by selective thresholding designed to remove the low texture content and then applying morphological techniques.     

An Automated Three-Dimensional Detection and Segmentation Method for Touching Cells by Integrating Concave Points Clustering and Random Walker Algorithm

Characterizing cytoarchitecture is crucial for understanding brain functions and neural diseases. In neuroanatomy, it is an important task to accurately extract cell populations'' centroids and contours. Recent advances have permitted imaging at single cell resolution for an entire mouse brain using the Nissl staining method. However, it is difficult to precisely segment numerous cells, especially those cells touching each other. As presented herein, we have developed an automated three-dimensional detection and segmentation method applied to the Nissl staining data, with the following two key steps: 1) concave points clustering to determine the seed points of touching cells; and 2) random walker segmentation to obtain cell contours. Also, we have evaluated the performance of our proposed method with several mouse brain datasets, which were captured with the micro-optical sectioning tomography imaging system, and the datasets include closely touching cells. Comparing with traditional detection and segmentation methods, our approach shows promising detection accuracy and high robustness.     

Modelling of global boundary effects on harmonic motion imaging of soft tissues

Biomechanical imaging techniques have been developed for soft tissue characterisation and detection of breast tumours. Harmonic motion imaging (HMI) uses a focused ultrasound technology to generate a harmonic radiation force in a localised region inside a soft tissue. The resulting dynamic response is used to map the local distribution of the mechanical properties of the tissue. In this study, a finite element (FE) model is developed to investigate the effect of global boundary conditions on the dynamic response of a soft tissue during HMI. The direct-solution steady-state dynamic analysis procedure is used to compute the harmonic displacement amplitude in FE simulations. The model is parameterised in terms of boundary conditions and viscoelastic properties, and the corresponding raster-scan displacement amplitudes are captured to examine its response. The effect of the model's global dimensions on the harmonic response is also investigated. It is observed that the dynamic response of soft tissue with high viscosity is independent of the global boundary conditions for regions remote to the boundary; thus, it can be subjected to local analysis to estimate the underlying mechanical properties. However, the dynamic response is sensitive to global boundary conditions for tissue with low viscosity or regions located near to the boundary.     

抑郁症患者的脑CT灌注成像特征与认知功能的相关性

摘要 目的：探讨抑郁症患者的脑CT灌注成像特征与认知功能的相关性。方法：选取我院2020年1月到2023年1月收治的90例抑郁症患者作为研究对象,将其分为观察组,另选取同期来我院体检的90名健康志愿者作为对照组。收集所有受检者脑CT灌注成像检查数据,分析抑郁症患者的脑CT灌注成像特征,并建立受试者工作特征（ROC）曲线分析脑CT灌注成像对抑郁症的诊断效能。随后对观察组和对照组受检者均进行认知功能评估,其中包括连线检测（TMT）、视觉再生测验（VRT）、言语流畅性测验（VF）、数字广度测验（DST）以及数字符号测验（SDMT）,并分析脑CT灌注成像与抑郁症认知功能的相关性。结果：观察组与对照组受检者rCBV、rCBF、MTT、TIP、右枕叶、左枕叶、右颞叶、左颞叶、右顶叶、左顶叶CT值对比无明显差异（P＞0.05）,观察组与对照组受检者右额叶、左额叶CT值对比差异显著,观察组明显低于对照组（P＜0.05）;90例抑郁症患者经过汉密尔顿抑郁量表（HAMD）评估后分数均＞20分,确定存在抑郁症状,脑CT灌注成像与HAMD评分诊断抑郁症的准确性、灵敏度、特异性、阳性预测值和阴性预测值对比无明显差异（P＞0.05）,脑CT灌注成像的曲线下面积为83.89,最佳诊断着色界限值为82.53%,HAMD评分的曲线下面积为84.26,最佳诊断着色界限值为87.57%;观察组与对照组受检者连线提笔数、连线错误数、视觉再生检测结果对比无明显差异（P＞0.05）,观察组与对照组受检者连线、言语流畅性、数字广度、数字符号检测结果对比差异显著（P＜0.05）;Spearman相关分析结果表明：连线提笔数、连线错误数、视觉再生与脑CT灌注参数均无明显相关性（P＞0.05）,连线、言语流畅性、数字广度、数字符号与rCBV、rCBF、MTT、TIP、右枕叶、左枕叶、右颞叶、左颞叶、右顶叶、左顶叶CT值无明显相关性（P＞0.05）,连线与右额叶、左额叶CT值呈负相关（P＜0.05）,言语流畅性、数字广度、数字符号与右额叶、左额叶CT值呈正相关（P＜0.05）。结论：抑郁症患者的脑CT灌注成像与健康群体呈现差异,其中右额叶、左额叶差异情况最为显著,提示抑郁症患者可能存在大脑额叶功能改变,另外,抑郁症患者的大脑额叶功能与认知功能变化具有明显相关性。     

640 层CT 对肝癌碘油栓塞沉积不良的临床分析

目的:探讨640层CT对肝癌碘油栓塞沉积不良患者治疗方案的临床指导。方法:21例富血供肝癌碘油动脉栓塞后,复查肝脏CT病灶内碘油沉积不良患者,用640层螺旋CT行CT灌注成像、CT动脉成像检查。结果:21例碘油沉积不良病灶内仍有动脉血供18例,坏死3例,18例有动脉血供病灶由肝动脉供血6例,膈下动脉供血3例,肠系膜上动脉供血4例,右侧副肾动脉供血1例,胃左动脉供血2例,右肾动脉供血2例。结论:640层螺旋CT灌注成像、CT动脉成像,可以准确显示肿瘤病灶碘油栓塞后肿瘤的残留与坏死,特别能精确判断肿瘤病灶血供起源情况,对再次介入治疗具有重要价值。     

不同探测距离对光声成像的影响

为了研究不同探测距离对光声成像的影响,采用了线性扫描和滤波反投影算法,得出了吸收体间距相对探测距离越大,则成像亮度差异明显,吸收体远离探测器,则重建图像变形很明显.采用了光声信号衰减补偿的方法,对前者重建图像取域值,对后者采用旋转扫描重建,均得到了较好的图像质量.该研究结果对光声成像探测距离的合理选择和成像效果评估具有...     

The SiFi-CC project – Feasibility study of a scintillation-fiber-based Compton camera for proton therapy monitoring

One of the big challenges for proton therapy is the development of tools for online monitoring of the beam range, which are suited to operate in clinical conditions and can be included in the clinical practice. A Compton camera based on stacks of heavy scintillating fibers used for prompt-gamma imaging is a promising approach for this task. It provides full, three-dimensional information on the deposited dose distribution while showing a high detection efficiency and rate capability due to its high granularity. The investigation of the rate capability and detection efficiency of such a camera under clinical conditions by means of Geant4 simulations is presented along with the event construction algorithm. The results hint towards a very low pile-up rate in the detector and a relatively high detection efficiency, so that imaging of a single proton beam spot appears to be an achievable goal.     

Imaging Non-Specific Wrist Pain: Interobserver Agreement and Diagnostic Accuracy of SPECT/CT,MRI, CT,Bone Scan and Plain Radiographs

Purpose

Chronic hand and wrist pain is a common clinical issue for orthopaedic surgeons and rheumatologists. The purpose of this study was 1. To analyze the interobserver agreement of SPECT/CT, MRI, CT, bone scan and plain radiographs in patients with non-specific pain of the hand and wrist, and 2. to assess the diagnostic accuracy of these imaging methods in this selected patient population.

Materials and Methods

Thirty-two consecutive patients with non-specific pain of the hand or wrist were evaluated retrospectively. All patients had been imaged by plain radiographs, planar early-phase imaging (bone scan), late-phase imaging (SPECT/CT including bone scan and CT), and MRI. Two experienced and two inexperienced readers analyzed the images with a standardized read-out protocol. Reading criteria were lesion detection and localisation, type and etiology of the underlying pathology. Diagnostic accuracy and interobserver agreement were determined for all readers and imaging modalities.

Results

The most accurate modality for experienced readers was SPECT/CT (accuracy 77%), followed by MRI (56%). The best performing, though little accurate modality for inexperienced readers was also SPECT/CT (44%), followed by MRI and bone scan (38% each). The interobserver agreement of experienced readers was generally high in SPECT/CT concerning lesion detection (kappa 0.93, MRI 0.72), localisation (kappa 0.91, MRI 0.75) and etiology (kappa 0.85, MRI 0.74), while MRI yielded better results on typification of lesions (kappa 0.75, SPECT/CT 0.69). There was poor agreement between experienced and inexperienced readers in SPECT/CT and MRI.

Conclusions

SPECT/CT proved to be the most helpful imaging modality in patients with non-specific wrist pain. The method was found reliable, providing high interobserver agreement, being outperformed by MRI only concerning the typification of lesions. We believe it is beneficial to integrate SPECT/CT into the diagnostic imaging algorithm of chronic wrist pain.     

Bayesian spatiotemporal modeling on complex-valued fMRI signals via kernel convolutions

We propose a model-based approach that combines Bayesian variable selection tools, a novel spatial kernel convolution structure, and autoregressive processes for detecting a subject's brain activation at the voxel level in complex-valued functional magnetic resonance imaging (CV-fMRI) data. A computationally efficient Markov chain Monte Carlo algorithm for posterior inference is developed by taking advantage of the dimension reduction of the kernel-based structure. The proposed spatiotemporal model leads to more accurate posterior probability activation maps and less false positives than alternative spatial approaches based on Gaussian process models, and other complex-valued models that do not incorporate spatial and/or temporal structure. This is illustrated in the analysis of simulated data and human task-related CV-fMRI data. In addition, we show that complex-valued approaches dominate magnitude-only approaches and that the kernel structure in our proposed model considerably improves sensitivity rates when detecting activation at the voxel level.     

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images

Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells.     

CT、常规MRI序列和SWI诊断弥漫性轴索脑损伤比较

目的：探讨弥漫性轴索损伤（DAI）的CT、常规MRI序列和磁敏感加权成像（SWI）表现与诊断价值。方法：回顾分析42例DAI患者的影像资料,分析、比较CT、MRI和SWI的信号特征及脑内病灶显示率。结果：SWI显示病灶最多、最敏感;脑CT扫描次之;常规MRI序列敏感性差,只有部分病灶显示。结论：CT、MRI和SWI对DAI早期诊断、治疗及评价预后具有重要参考价值,SWI是诊断DAI最有效的首选影像学检查方法。     

激光散斑成像技术在脑科学研究中的应用

激光散斑衬比成像(laser speckle contrast imaging,LSCI)是一种非扫描式实时血流动力学成像技术,具有高分辨率、快速实时成像、非接触、仪器结构较简单等优势.尽管由于深度分辨率的限制,LSCI主要用于浅表组织测量,但其在神经疾病、皮肤病等领域的基础研究及临床应用中展现出良好的应用潜力.本文简要介绍了激光散斑衬比成像技术的基本原理与技术进展,综述其在脑卒中、吸毒成瘾、阿尔茨海默病等脑疾病及其他脑科学应用中的研究进展,并展望其发展前景.     

VCTDSA联合CT灌注成像在急性缺血性卒中诊断运用探究

目的：探讨64层容积CT数字减影血管造影（Volume computed tomography digital subtraction angiography, VCTDSA）联合CT灌注成像在急性缺血性卒中诊断价值。方法：回顾性分析45例临床确诊为急性缺血性卒中患者的临床资料,分别给予VCTDSA与CT灌注成像处理,分析这两种技术对急性缺血性卒中患者的诊断敏感性和特异性。结果：45例患者检查有颅内有不同部位出血灶,多见于脑室,均伴有不同程度的异常血管网形成,其中VCTDSA图像质量优于CT灌注成像,VCTDSA较DSA可准确显示和测量动静脉瘘口大小,VCTDSA与MRA在瘤体长轴、瘤颈的比较中无显著性差异。结论：与其他减影CTA比较,VCTDSA联合CT灌注成像在急性缺血性卒中患者的诊断中具有优势。