Volume 35, Issue 12

This paper presents a robust and fully automatic filter-based approach for retinal vessel segmentation. We propose new filters based on 3D rotating frames in so-called orientation scores, which are functions on the Lie-group domain of positions and orientations ℝ 2 × S 1 . By means of a wavelet-type transform, a 2D image is lifted to a 3D orientation score, where elongated structures are disentangled into their corresponding orientation planes. In the lifted domain ℝ 2 × S 1 , vessels are enhanced by means of multi-scale second-order Gaussian derivatives perpendicular to the line structures. More precisely, we use a left-invariant rotating derivative (LID) frame, and a locally adaptive derivative (LAD) frame. The LAD is adaptive to the local line structures and is found by eigensystem analysis of the left-invariant Hessian matrix (computed with the LID). After multi-scale filtering via the LID or LAD in the orientation score domain, the results are projected back to the 2D image plane giving us the enhanced vessels. Then a binary segmentation is obtained through thresholding. The proposed methods are validated on six retinal image datasets with different image types, on which competitive segmentation performances are achieved. In particular, the proposed algorithm of applying the LAD filter on orientation scores (LAD-OS) outperforms most of the state-of-the-art methods. The LAD-OS is capable of dealing with typically difficult cases like crossings, central arterial reflex, closely parallel and tiny vessels. The high computational speed of the proposed methods allows processing of large datasets in a screening setting.

本文提出了一种鲁棒且全自动的基于滤波器的视网膜血管分割方法。我们提出了基于所谓方向得分中的3D旋转框架的新滤波器，方向得分是位置和方向李群域ℝ²×S¹上的函数。通过小波型变换，将2D图像提升到3D方向得分，其中细长结构被分解到其对应的方向平面中。在提升域ℝ²×S¹中，通过垂直于线结构的多尺度二阶高斯导数增强血管。更精确地说，我们使用了左不变旋转导数（LID）框架和局部自适应导数（LAD）框架。LAD对局部线结构自适应，通过左不变Hessian矩阵（使用LID计算）的特征系统分析得到。通过在方向得分域中使用LID或LAD进行多尺度滤波后，结果投影回2D图像平面，得到增强的血管。然后通过阈值化得到二值分割。所提出的方法在六个具有不同图像类型的视网膜图像数据集上进行了验证，取得了具有竞争力的分割性能。特别是，所提出的在方向得分上应用LAD滤波器（LAD-OS）的算法优于大多数现有方法。LAD-OS能够处理典型困难情况，如交叉、中央动脉反射、紧密平行和微小的血管。所提出的方法计算速度快，允许在筛选设置中处理大型数据集。

Structural magnetic resonance imaging (MRI) is a very popular and effective technique used to diagnose Alzheimer’s disease (AD). The success of computer-aided diagnosis methods using structural MRI data is largely dependent on the two time-consuming steps: 1) nonlinear registration across subjects, and 2) brain tissue segmentation. To overcome this limitation, we propose a landmark-based feature e...

结构磁共振成像（MRI）是一种非常流行且有效的用于诊断阿尔茨海默病（AD）的技术。使用结构MRI数据的计算机辅助诊断方法的成功很大程度上依赖于两个耗时的步骤：1）受试者之间的非线性配准，2）脑组织分割。为了克服这一限制，我们提出了一种基于地标的特征...

This work develops a material reconstruction method for spectral CT, namely Total Image Constrained Material Reconstruction (TICMR), to maximize the utility of projection data in terms of both spectral information and high signal-to-noise ratio (SNR). This is motivated by the following fact: when viewed as a spectrally-integrated measurement, the projection data can be used to reconstruct a total ...

本文开发了一种用于光谱CT的材料重建方法，即总图像约束材料重建（TICMR），旨在最大化投影数据在光谱信息和高信噪比（SNR）方面的效用。其动机源于以下事实：当投影数据被视为光谱积分测量时，可用于重建总图像...

This paper describes a novel generative model for the synthesis of multi-modal medical images of pathological cases based on a single label map. Our model builds upon i) a generative model commonly used for label fusion and multi-atlas patch-based segmentation of healthy anatomical structures, ii) the Modality Propagation iterative strategy used for a spatially-coherent synthesis of subject-specif...

本文描述了一种基于单一标签图生成病理病例多模态医学图像的新型生成模型。我们的模型建立在以下基础上：i) 一种常用于健康解剖结构标签融合和多图谱块分割的生成模型；ii) 模态传播迭代策略，用于空间一致地合成特定主体的多模态图像。

Brain atlases are an essential component in understanding the dynamic cerebral development, especially for the early postnatal period. However, longitudinal atlases are rare for infants, and the existing ones are generally limited by their fuzzy appearance. Moreover, since longitudinal atlas construction is typically performed independently over time, the constructed atlases often fail to preserve...

脑图谱是理解动态脑发育的重要组成部分，尤其是对于早期产后阶段。然而，婴儿的纵向图谱很少，现有的图谱通常受到模糊外观的限制。此外，由于纵向图谱构建通常是随时间独立进行的，构建的图谱往往无法保持一致性……

This paper proposes a novel imaging biomarker of lung cancer relapse from 3-D texture analysis of CT images. Three-dimensional morphological nodular tissue properties are described in terms of 3-D Riesz-wavelets. The responses of the latter are aggregated within nodular regions by means of feature covariances, which leverage rich intra- and inter-variations of the feature space dimensions. When co...

本文提出了一种从CT图像的三维纹理分析中预测肺癌复发的新型影像生物标志物。三维形态结节组织特性通过三维Riesz小波描述。通过特征协方差在结节区域内聚合这些响应，充分利用特征空间维度的丰富内外部变化。当与...

Prostate cancer (PCa) recurrences are often predicted by assessing the status of surgical margins (SM)– positive surgical margins (PSM) increase the chances of biochemical recurrence by 2-4 times which may lead to PCa recurrence. To this end, an electrical impedance acquisition system with a microendoscopic probe was employed in an ex-vivo study of human prostates. This system measures the tissue ...

前列腺癌（PCa）复发通常通过评估手术切缘（SM）状态来预测——阳性手术切缘（PSM）使生化复发几率增加2-4倍，可能导致PCa复发。为此，在离体人前列腺研究中采用了带有显微内窥镜探头的电阻抗采集系统。该系统测量组织...

Fiber bundles stemming from tractography algorithms contain many streamlines. They require therefore a great amount of computer memory and computational resources to be stored, visualised and processed. We propose an approximation scheme for fiber bundles which results in a parsimonious representation of weighted prototypes. Prototypes are chosen among the streamlines and they represent groups of ...

源自纤维追踪算法的纤维束包含许多流线，因此需要大量的计算机内存和计算资源来存储、可视化和处理。我们提出了一种纤维束近似方案，该方案通过加权原型实现简约表示。原型从流线中选择，代表各组...

The computation of model matrix in the iterative imaging reconstruction process is crucial for the quantitative photoacoustic tomography (PAT). However, it is challenging to establish an outstanding model matrix to improve the overall imaging quality in PAT due to the noisy signal acquisition and inevitable artifacts. In this work, we present a novel method, named as the curve-driven-based model-m...

在迭代成像重建过程中，模型矩阵的计算对于定量光声断层成像（PAT）至关重要。然而，由于噪声信号采集和不可避免的伪影，建立出色的模型矩阵以提高PAT的整体成像质量具有挑战性。在这项工作中，我们提出了一种新方法，称为基于曲线驱动的模型...

Statistical sub-pixel detection via the adaptive matched filter (AMF) has been shown to improve the molecular imaging sensitivity and specificity of optoacoustic (photoacoustic) imaging. Applied to multispectral optoacoustic tomography (MSOT), AMF assumes that the spatially-varying tissue spectra follow a multivariate Gaussian distribution, that the spectrum of the target molecule is precisely kno...

通过自适应匹配滤波器（AMF）的统计亚像素检测已被证明可以提高光声成像的分子成像灵敏度和特异性。应用于多光谱光声断层成像（MSOT），AMF假设空间变化的组织光谱遵循多变量高斯分布，目标分子的光谱精确已知...

Q-spoiling is the process of decoupling an MRI receive coil to protect the equipment and patient. Conventionally, Q-spoiling is performed using a PIN diode switch that draws significant current. In this work, a Q-spoiling technique using a depletion-mode Gallium Nitride HEMT device was developed for coil detuning at both 1.5 T and 3 T MRI. The circuits with conventional PIN diode Q-spoiling and th...

Q-spoiling是解耦MRI接收线圈以保护设备和患者的过程。传统上，Q-spoiling使用消耗大量电流的PIN二极管开关进行。在这项工作中，开发了一种使用耗尽模式氮化镓HEMT器件的Q-spoiling技术，用于1.5 T和3 T MRI的线圈失谐。采用传统PIN二极管Q-spoiling的电路和...

Diffusion weighted magnetic resonance imaging (DW-MR) is a powerful tool in imaging-based prostate cancer screening and detection. Endorectal coils are commonly used in DW-MR imaging to improve the signal-to-noise ratio (SNR) of the acquisition, at the expense of significant intensity inhomogeneities (bias field) that worsens as we move away from the endorectal coil. The presence of bias field can...

扩散加权磁共振成像（DW-MR）是前列腺癌筛查和检测中一种强大的成像工具。在DW-MR成像中，通常使用直肠内线圈来提高采集的信噪比（SNR），但代价是显著的强度不均匀性（偏置场），且随着远离直肠内线圈而恶化。偏置场的存在可能……

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