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2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro最新文献

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Spatiotemporal Bayesian cell population tracking and analysis with lineage construction 时空贝叶斯细胞群跟踪与谱系构建分析
Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541002
Luke M. A. Beaumont, James Wake, eld, J. Noble
Tracking of cell populations in vitro in time lapse microscopy images enables automatic high throughput spatiotemporal measurements of a range of cell cycle mechanics and dynamics. Both in clinical and academic environments, large scale cellular data analysis using such methods stands to facilitate a paradigm shift in approaches to understanding cell biology. In this paper, we present a novel approach to cell population tracking and segmentation. We employ the CONDENSATION algorithm in tandem with Fast Levels Sets and Exclusion Zones for robust tracking and pixel-accurate segmentation. The algorithm feeds its output to a lineage filter. The complete approach is validated in terms of its ability to track and identify nuclei, and by its success in detecting abnormalities in the length of mitosis.
在时间推移显微镜图像中对体外细胞群进行跟踪,可以对一系列细胞周期力学和动力学进行自动高通量时空测量。无论是在临床还是学术环境中,使用这种方法进行大规模细胞数据分析,都有助于在理解细胞生物学的方法上实现范式转变。在本文中,我们提出了一种新的细胞群跟踪和分割方法。我们采用冷凝算法与快速水平集和禁区串联进行鲁棒跟踪和像素精确分割。该算法将其输出馈送到沿袭过滤器。完整的方法在其跟踪和识别细胞核的能力方面得到了验证,并通过其成功地检测有丝分裂长度的异常。
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引用次数: 4
Axonal bouton modeling, detection and distribution analysis for the study of neural circuit organization and plasticity 用于神经回路组织和可塑性研究的轴突钮扣建模、检测和分布分析
Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4540958
Christina A. Hallock, I. Ozgunes, Ramamurthy Bhagavatula, G. Rohde, J. C. Crowley, C. E. Onorato, A. Mavalankar, A. Chebira, C. H. Tan, Markus Püschel, J. Kovacevic
We propose a novel method for axonal bouton modeling and automated detection in populations of labeled neurons, as well as bouton distribution analysis for the study of neural circuit organization and plasticity. Since axonal boutons are the presynaptic specializations of neural synapses, their locations can be used to determine the organization of neural circuitry, and in time-lapse studies, neural circuit dynamics. We propose simple geometric models for axonal boutons that account for variations in size, position, rotation and curvature of the axon in the vicinity of the bouton. We then use the normalized cross-correlation between the model and image data as a test statistic for bouton detection and position estimation. Thus, the problem is cast as a statistical detection problem where we can tune the algorithm parameters to maximize the probability of detection for a given probability of false alarm. For example, we can detect 81% of boutons with 9% false alarm from noisy, out of focus, images. We also present a novel method to characterize the orientation and elongation of a distribution of labeled boutons and we demonstrate its performance by applying it to a labeled data set.
我们提出了一种新的轴突钮扣建模和标记神经元群体自动检测方法,以及用于研究神经回路组织和可塑性的钮扣分布分析方法。由于轴突钮扣是神经突触的突触前特化,它们的位置可以用来确定神经回路的组织,并在延时研究中确定神经回路动力学。我们为轴突钮扣提出了简单的几何模型,该模型考虑了钮扣附近轴突的大小、位置、旋转和曲率的变化。然后,我们使用模型和图像数据之间的归一化互相关作为钮扣检测和位置估计的检验统计量。因此,这个问题被视为一个统计检测问题,我们可以调整算法参数,以最大化给定的假警报概率的检测概率。例如,我们可以从噪声、失焦图像中检测出81%的钮扣和9%的误报。我们还提出了一种新的方法来表征标记钮扣分布的方向和伸长,并通过将其应用于标记数据集来证明其性能。
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引用次数: 2
A new filter for spot extraction in n-dimensional biological imaging 一种新的n维生物成像斑点提取滤波器
Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541161
E. Biot, Elizabeth Crowell, H. Hofte, Y. Maurin, S. Vernhettes, P. Andrey
In confocal cellular imaging, fluorescent markers are used to label target structures. These elements of interest frequently appear as spots within a noisy background. Several algorithms have been proposed to extract spots in such conditions. However, specific methods are required when other structures are also labelled. In this paper, a new spot extraction filter is proposed to discriminate between spots and other structures using the shape of the local spatial intensity distribution. Preliminary results in the analysis of the intra-cellular distribution of the KORRIGAN1 protein in plant cells are presented. Very low detection error rates are reported.
在共聚焦细胞成像中,荧光标记物用于标记目标结构。这些感兴趣的元素经常在嘈杂的背景中以斑点的形式出现。已经提出了几种算法来提取这种情况下的斑点。然而,当其他结构也被标记时,需要特定的方法。本文提出了一种新的斑点提取滤波器,利用局部空间强度分布的形状来区分斑点和其他结构。本文介绍了植物细胞中KORRIGAN1蛋白的细胞内分布分析的初步结果。报告的检测错误率非常低。
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引用次数: 21
Variability of the relative corpus callosum cross sectional area between dyslexic and normally developed brains 阅读困难症和正常发育的大脑相对胼胝体横截面积的差异
Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541026
N. El-Zehiry, M. Casanova, Adel Said Elmaghraby
Minicolumnar disturbance is a common feature to both dyslexic and autistic brains. This paper is motivated by the persistent need to investigate the effect of minicolumnar disturbance on the magnetic resonance images of the brain. This will serve as a preliminary step to develop a non-invasive methodology to discriminate between the diseases based on the MRI findings. In this paper, we investigate the variability of the ratio between the corpus callosum cross sectional area and the total brain intracranial volume between two groups; a group of dyslexic patients and another group of normal controls. The results show that this ratio differs significantly between the two groups and that it can be used as a discriminatory feature between dyslexic brains and typically developed ones.
小柱状障碍是诵读困难症和自闭症大脑的共同特征。本文的动机是持续需要研究微小柱状干扰对大脑磁共振图像的影响。这将作为开发一种基于MRI结果区分疾病的非侵入性方法的初步步骤。本研究探讨了两组患者胼胝体横截面积与脑总颅内容积之比的变异性;一组是诵读困难患者,另一组是正常对照。结果表明,这一比例在两组之间存在显著差异,这可以作为阅读困难大脑和正常发育大脑之间的区别特征。
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引用次数: 5
Visualizing morphogenesis and growth by temporal interpolation of surface-based 3D atlases 通过基于表面的三维地图集的时间插值可视化形态发生和生长
Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541123
Chavdar Papazov, V. J. Dercksen, H. Lamecker, H. Hege
Image-based 3D atlases have been proven to be very useful in biological and medical research. They serve as spatial reference systems that enable researchers to integrate experimental data in a spatially coherent way and thus to relate diverse data from different experiments. Typically such atlases consist of tissue-separating surfaces. The next step are 4D atlases that provide insight into temporal development and spatio- temporal relationships. Such atlases are based on time series of 3D images and related 3D models. We present work on temporal interpolation between such 3D atlases. Due to the morphogenesis of tissues during biological development, the topology of the non-manifold surfaces may vary between subsequent time steps. For animation therefore a smooth morphing between non-manifold surfaces with different topology is needed.
基于图像的三维地图集已被证明在生物和医学研究中非常有用。它们作为空间参考系统,使研究人员能够以空间连贯的方式整合实验数据,从而将来自不同实验的不同数据联系起来。这种地图集通常由组织分离表面组成。下一步是4D地图集,提供对时间发展和时空关系的洞察。这样的地图集是基于3D图像的时间序列和相关的3D模型。我们介绍了这种三维地图集之间的时间插值工作。由于生物发育过程中组织的形态发生,非流形表面的拓扑结构可能在随后的时间步骤之间发生变化。因此,对于动画来说,需要在具有不同拓扑结构的非流形表面之间进行平滑变形。
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引用次数: 0
Effective voigt model estimation using multiple random starting values and parameter bounds settings for in vivo hepatic 1H magnetic resonance spectroscopic data 使用多个随机起始值和参数边界设置对体内肝脏1H磁共振光谱数据进行有效voigt模型估计
Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541300
H. Ratiney, A. Bucur, M. Sdika, O. Beuf, F. Pilleul, S. Cavassila
In vivo hepatic 1H lineshapes modeled by the complex Voigt function are desirable to reduce systematic error and obtain accurate fits. However, the optimization procedure becomes challenging when the peak resonances overlap and the proportion of Gaussian to Lorentzian dampings is a priori unknown. In this context, nonlinear least-squares algorithms generally invoked in Magnetic Resonance Spectroscopy quantification are highly sensitive to the starting values and parameter bounds. To alleviate this sensitivity, multiple random starting values and parameter bounds settings are used to generate candidate solutions. The "best fit" fulfilling requirements on the cost function and damping factor final values is then selected among them. Monte Carlo studies and an in vivo hepatic 1H signal quantification demonstrated the relevance of the proposed strategy.
通过复杂Voigt函数建模的体内肝脏1H线形是减少系统误差和获得准确拟合的理想选择。然而,当峰值共振重叠且高斯阻尼与洛伦兹阻尼的比例先验未知时,优化过程变得具有挑战性。在这种情况下,通常在磁共振波谱定量中使用的非线性最小二乘算法对起始值和参数边界高度敏感。为了减轻这种敏感性,使用多个随机起始值和参数边界设置来生成候选解。然后从中选择满足成本函数和阻尼因子最终值要求的“最佳拟合”。蒙特卡罗研究和体内肝脏1H信号量化证明了所提出策略的相关性。
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引用次数: 11
Detection and characterization of the tumor change between two FDG PET scans using parametric imaging 使用参数成像检测和表征两次FDG PET扫描之间的肿瘤变化
Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4540922
H. Necib, M. Dusart, B. Vanderlinden, I. Buvat
Patient follow-up based on PET scans is a promising approach for early assessment of tumor response and for detection of tumor recurrence. In this work, we introduce a parametric imaging method to detect and analyze the tumor changes between 2 consecutive PET scans. Fifteen pairs of consecutives PET/CT images obtained during the course of lung cancer patient monitoring were considered. For each pair, after CT- based registration of the PET images, the two PET datasets were subtracted. A biparametric graph of subtracted voxel values versus voxel values in the first scan was obtained. A model- based analysis of this graph was used to identify the tumor voxels in which significant changes occurred between the 2 scans, and yielded indices characterizing the changes. In our patients, the proposed approach correctly identified all tumor changes as confirmed using a conventional analysis. In addition, the parametric imaging approach can reveal heterogeneities in tumor response and does not require the preliminary identification of the tumors.
基于PET扫描的患者随访是早期评估肿瘤反应和检测肿瘤复发的一种有希望的方法。在这项工作中,我们引入了一种参数化成像方法来检测和分析连续两次PET扫描之间的肿瘤变化。考虑在肺癌患者监测过程中连续获得的15对PET/CT图像。对于每一对,在基于CT的PET图像配准后,将两个PET数据集相减。获得了第一次扫描中减去的体素值与体素值的双参数图。对该图进行基于模型的分析,以确定两次扫描之间发生显著变化的肿瘤体素,并得出表征变化的指标。在我们的患者中,所提出的方法正确地识别了所有的肿瘤变化,正如使用传统分析证实的那样。此外,参数化成像方法可以揭示肿瘤反应的异质性,不需要对肿瘤进行初步识别。
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引用次数: 6
Automatic cell recognition in immunohistochemical gastritis stains using sequential thresholding and SVM network 基于序列阈值和支持向量机网络的免疫组化胃炎染色细胞自动识别
Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4541160
T. Markiewicz, C. Jochymski, R. Koktysz, W. Kozlowski
The paper presents program for automatic cell recognition and counting in selected immunohistochemical stains in the gastritis diseases. It is applied to cytoplasm reactivity markers, such as chromogranin A, serotonin and somatostatin antibodies. The program uses the sequential thresholding algorithm in combination with artificial neural network of support vector machine (SVM) type, to recognize the nuclei of the separated cells. The constructed algorithm imitates the human view of the image. The support vector machine is used for recognition of the immunoreactivity of the separated cell. The results corresponding to the exemplary images, confirm good accuracy, comparable to the human expert.
本文介绍了胃炎疾病免疫组化染色细胞自动识别和计数程序。它适用于细胞质反应性标记物,如嗜铬粒蛋白A、血清素和生长抑素抗体。该程序采用序列阈值算法与支持向量机(SVM)型人工神经网络相结合,对分离细胞的细胞核进行识别。所构建的算法模拟了人类对图像的看法。支持向量机用于识别分离细胞的免疫反应性。结果与示例图像相对应,证实准确性好,可与人类专家相媲美。
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引用次数: 9
3D cardiac motion tracking using Robust Point Matching and meshless deformable models 使用鲁棒点匹配和无网格变形模型的3D心脏运动跟踪
Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4540987
Ting Chen, Xiaoxu Wang, Dimitris N. Metaxas, L. Axel
We propose a novel 3D motion estimation approach integrating the robust point matching (RPM) and meshless deformable models. In our study, we first use the Gabor filters to generate phase maps of short axis (SA) and long axis (LA) tagged MRI sequences. Then we use the RPM to track the heart motion sparsely at intersections of tag grids in these image sequences, using both intensity gradient and phase information. Next, the new meshless deformable model is used to recover the dense 3D motion of the myocardium temporally during the cardiac cycle. The deformable model is driven by external forces computed at tag intersections based on the RPM motion tracking and keeps a consistent but flexible topology during the deformation using internal constraint forces calculated by the moving least squares (MLS) method. The deformable model recovers the global deformation of the LV such as rotation, contraction and twisting by integrating global deformation parameters over the volume. The new model avoids the singularity problem of mesh-based deformable models and is capable of tracking deformation efficiently with the sparse external forces derived from tagging line intersections. We test the performance of the new approach on in vivo heart data of healthy subjects and patients. The experimental results show that our new method can fully recover the myocardium motion and strain in 3D.
提出了一种结合鲁棒点匹配和无网格变形模型的三维运动估计方法。在我们的研究中,我们首先使用Gabor滤波器来生成短轴(SA)和长轴(LA)标记的MRI序列的相位图。然后,我们使用RPM在这些图像序列中标记网格的交叉点稀疏跟踪心脏运动,同时使用强度梯度和相位信息。然后,利用新的无网格可变形模型暂时恢复心肌在心动周期中密集的三维运动。该变形模型基于RPM运动跟踪,由标签交点处计算的外力驱动,并利用运动最小二乘(MLS)方法计算的内力在变形过程中保持一致的柔性拓扑。可变形模型通过对体积上的全局变形参数进行积分,恢复LV的旋转、收缩、扭转等全局变形。该模型避免了基于网格的变形模型的奇异性问题,能够利用标记线相交产生的稀疏外力有效地跟踪变形。我们在健康受试者和患者的体内心脏数据上测试了新方法的性能。实验结果表明,该方法可以完全恢复心肌运动和应变的三维图像。
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引用次数: 6
Automatic tuning of a graph-based image segmentation method for digital mammography applications 数字乳腺摄影应用中基于图形的图像分割方法的自动调整
Pub Date : 2008-05-14 DOI: 10.1109/ISBI.2008.4540939
Hirotaka Susukida, Fei Ma, M. Bajger
Mammogram segmentation tasks underpin a wide range of registration, temporal analysis and detection algorithms. Unfortunately, finding an accurate, robust and efficient segmentation still remains a challenging problem in mammography. A recent segmentation technique, based on minimum spanning trees (MST segmentation), is known to be robust to typical mammogram distortions and computationally efficient. This method captures both local and global image information but the balance requires choosing a parameter. So far no automatic procedure to estimate this parameter has been proposed and the value was determined experimentally. In this paper a segmentation evaluation criterion, based on a measure of image entropy, is used to automatically optimize the granularity of an MST-based segmentation. The method is tested on a set of 82 random images taken from a commonly used mammogram database. The results show a dramatic improvement in the accuracy of a MST segmentation tuned up using the entropy-based criterion.
乳房x光片分割任务支持广泛的配准,时间分析和检测算法。不幸的是,找到一个准确,稳健和有效的分割仍然是乳房x光检查的一个具有挑战性的问题。最近的一种基于最小生成树(MST分割)的分割技术被认为对典型的乳房x线照片失真具有鲁棒性和计算效率。该方法同时捕获局部和全局图像信息,但平衡需要选择一个参数。到目前为止,还没有提出自动估计该参数的程序,其值是通过实验确定的。本文提出了一种基于图像熵度量的分割评价准则,用于自动优化基于mst的分割粒度。该方法在一组82张随机图像上进行了测试,这些图像取自一个常用的乳房x光检查数据库。结果表明,使用基于熵的标准调整后的MST分割的准确性有了显着的提高。
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引用次数: 6
期刊
2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro
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