Volume 29, Issue 8

Microscopy cell image analysis is a fundamental tool for biological research. In particular, multivariate fluorescence microscopy is used to observe different aspects of cells in cultures. It is still common practice to perform analysis tasks by visual inspection of individual cells which is time consuming, exhausting and prone to induce subjective bias. This makes automatic cell image analysis essential for large scale, objective studies of cell cultures. Traditionally the task of automatic cell analysis is approached through the use of image segmentation methods for extraction of cells' locations and shapes. Image segmentation, although fundamental, is neither an easy task in computer vision nor is it robust to image quality changes. This makes image segmentation for cell detection semi-automated requiring frequent tuning of parameters. We introduce a new approach for cell detection and shape estimation in multivariate images based on the sliding band filter (SBF). This filter's design makes it adequate to detect overall convex shapes and as such it performs well for cell detection. Furthermore, the parameters involved are intuitive as they are directly related to the expected cell size. Using the SBF filter we detect cells' nucleus and cytoplasm location and shapes. Based on the assumption that each cell has the same approximate shape center in both nuclei and cytoplasm fluorescence channels, we guide cytoplasm shape estimation by the nuclear detections improving performance and reducing errors. Then we validate cell detection by gathering evidence from nuclei and cytoplasm channels. Additionally, we include overlap correction and shape regularization steps which further improve the estimated cell shapes. The approach is evaluated using two datasets with different types of data: a 20 images benchmark set of simulated cell culture images, containing 1000 simulated cells; a 16 images Drosophila melanogaster Kc167 dataset containing 1255 cells, stained for DNA and actin. Both image datasets present a difficult problem due to the high variability of cell shapes and frequent cluster overlap between cells. On the Drosophila dataset our approach achieved a precision/recall of 95%/69% and 82%/90% for nuclei and cytoplasm detection respectively and an overall accuracy of 76%.

显微细胞图像分析是生物学研究的基本工具。特别是，多变量荧光显微镜用于观察培养细胞的不同方面。目前，通过视觉检查单个细胞来执行分析任务仍然是常见做法，这既耗时又容易产生主观偏差。这使得自动细胞图像分析对于大规模、客观的细胞培养研究至关重要。传统上，自动细胞分析的任务通过使用图像分割方法提取细胞的位置和形状来实现。图像分割虽然是基础，但在计算机视觉中并非易事，也不鲁棒于图像质量变化。这使得用于细胞检测的图像分割半自动化，需要频繁调整参数。本文提出了一种基于滑动带滤波器（SBF）的多变量图像中细胞检测和形状估计的新方法。该滤波器的设计使其足以检测整体凸形状，因此在细胞检测中表现良好。此外，涉及的参数直观，因为它们直接与预期的细胞大小相关。使用SBF滤波器，我们检测细胞核和细胞质的位置和形状。基于每个细胞在细胞核和细胞质荧光通道中具有近似相同形状中心的假设，我们通过核检测指导细胞质形状估计，提高性能并减少误差。然后通过从核和细胞质通道收集证据来验证细胞检测。此外，我们还包括重叠校正和形状正则化步骤，进一步改进估计的细胞形状。该方法使用两个不同类型的数据集进行评估：一个包含1000个模拟细胞的20张模拟细胞培养图像基准集；一个包含1255个细胞、标记DNA和肌动蛋白的16张黑腹果蝇Kc167数据集。由于细胞形状的高度变异和细胞之间频繁的簇重叠，这两个图像数据集都提出了难题。在果蝇数据集上，我们的方法在核检测和细胞质检测上分别达到了95%/69%和82%/90%的精确率/召回率，总体准确率为76%。

Magnetic resonance imaging (MRI) is emerging as the method of choice for measuring cartilage loss in osteoarthritis (OA), but current methods of analysis are imperfect for therapeutic clinical trials. In this paper, we present and evaluate, in two multicenter multivendor studies, a new method for anatomically corresponded regional analysis of cartilage (ACRAC) that allows analysis of knee cartilag...

磁共振成像（MRI）正在成为测量骨关节炎（OA）中软骨损失的首选方法，但当前的分析方法对于治疗性临床试验并不完美。在本文中，我们在两项多中心、多供应商研究中提出并评估了一种新的解剖对应区域软骨分析（ACRAC）方法，该方法允许分析膝关节软骨...

There is an ongoing debate on how to model diffusivity in fiber crossings. We propose an optimization framework for the selection of a dual tensor model and the set of diffusion weighting parameters b, such that both the diffusion shape and orientation parameters can be precisely as well as accurately estimated. For that, we have adopted the Cramér-Rao lower bound (CRLB) on the variance of the mod...

关于如何在纤维交叉中模拟扩散率，目前存在持续的争论。我们提出了一种优化框架，用于选择双张量模型以及扩散加权参数b的集合，使得扩散形状和方向参数都能被精确且准确地估计。为此，我们采用了克拉美-罗下界（CRLB）对模...的方差进行约束。

Magnetic resonance tagging makes it possible to measure the motion of tissues such as muscles in the heart and tongue. The harmonic phase (HARP) method largely automates the process of tracking points within tagged MR images, permitting many motion properties to be computed. However, HARP tracking can yield erroneous motion estimates due to 1) large deformations between image frames, 2) through-pl...

磁共振标记使得测量心脏和舌头等组织的运动成为可能。谐波相位（HARP）方法大大自动化了标记磁共振图像中点的跟踪过程，允许计算许多运动属性。然而，HARP跟踪可能由于1）图像帧之间的大形变，2）穿过...

Projection data incompleteness arises in many situations relevant to X-ray computed tomography (CT) imaging. We propose a penalized maximum likelihood statistical sinogram restoration approach that incorporates the Helgason–Ludwig (HL) consistency conditions to accommodate projection data incompleteness. Image reconstruction is performed by the filtered-backprojection (FBP) in a second step. In ou...

投影数据不完整性在许多与X射线计算机断层扫描（CT）成像相关的情况下出现。我们提出了一种惩罚最大似然统计正弦图恢复方法，该方法结合了Helgason-Ludwig（HL）一致性条件以适应投影数据不完整性。图像重建通过第二步中的滤波反投影（FBP）进行。在我们的...

We introduce a new model-based approach for automatic quantification of colocalizations in multichannel 3D microscopy images. The approach uses different 3D parametric intensity models in conjunction with a model fitting scheme to localize and quantify subcellular structures with high accuracy. The central idea is to determine colocalizations between different channels based on the estimated geome...

我们介绍了一种新的基于模型的方法，用于自动量化多通道3D显微镜图像中的共定位。该方法结合使用不同的3D参数强度模型和模型拟合方案，以高精度定位和定量亚细胞结构。核心思想是基于估计的几何结构确定不同通道之间的共定位...

Free-breathing image acquisition is desirable in first-pass gadolinium-enhanced magnetic resonance imaging (MRI), but the breathing movements hinder the direct automatic analysis of the myocardial perfusion and qualitative readout by visual tracking. Nonrigid registration can be used to compensate for these movements but needs to deal with local contrast and intensity changes with time. We propose...

在首次通过钆增强磁共振成像（MRI）中，自由呼吸图像采集是可取的，但呼吸运动会阻碍心肌灌注的直接自动分析和通过视觉追踪的定性读取。非刚性配准可用于补偿这些运动，但需要处理随时间变化的局部对比度和强度变化。我们提出...

We present a new application of multispectral analysis for subcellular measurement of multiple proteins in formalin-fixed paraffin embedded tissue and cells. Typically, the targets of interest are present in the same or spatially overlapping cellular compartments. Such co-localization can complicate analysis and interpretation of the images obtained using traditional fluorescence, especially when ...

我们提出了一种多光谱分析的新应用，用于对福尔马林固定石蜡包埋的组织和细胞中的多种蛋白质进行亚细胞测量。通常，感兴趣的目标存在于相同或空间重叠的细胞区室中。这种共定位会使使用传统荧光获得的图像分析和解释复杂化，尤其是在……

In this paper, we present a novel approach for a trainable rotation invariant detection of complex structures in 3D microscopic multichannel data using a nonlinear filter approach. The basic idea of our approach is to compute local features in a window around each 3D position and map these features by means of a nonlinear mapping onto new local harmonic descriptors of the local window. These local...

在本文中，我们提出了一种新颖的方法，用于在3D显微多通道数据中通过可训练的旋转不变检测复杂结构，采用非线性滤波器方法。该方法的基本思想是在每个3D位置周围的窗口中计算局部特征，并通过非线性映射将这些特征映射到局部窗口的新局部谐波描述符上。这些局部...

This study aimed to evaluate three image fidelity metrics of different computational principles-peak signal-to-noise ratio (PSNR), high-dynamic range visual difference predictor (HDR-VDP), and multiscale structural similarity (MS-SSIM)-in measuring the fidelity of JPEG2000 compressed abdomen computed tomography images from a viewpoint of visually lossless compression. Three hundred images with 0.6...

本研究旨在从视觉无损压缩的角度，评估三种不同计算原理的图像保真度度量——峰值信噪比（PSNR）、高动态范围视觉差异预测器（HDR-VDP）和多尺度结构相似性（MS-SSIM）——在衡量JPEG2000压缩腹部计算机断层扫描图像保真度方面的表现。使用了300幅0.6...

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