Volume 37, Issue 8

Automatic segmentation of abdominal anatomy on computed tomography (CT) images can support diagnosis, treatment planning, and treatment delivery workflows. Segmentation methods using statistical models and multi-atlas label fusion (MALF) require inter-subject image registrations, which are challenging for abdominal images, but alternative methods without registration have not yet achieved higher accuracy for most abdominal organs. We present a registration-free deep-learning-based segmentation algorithm for eight organs that are relevant for navigation in endoscopic pancreatic and biliary procedures, including the pancreas, the gastrointestinal tract (esophagus, stomach, and duodenum) and surrounding organs (liver, spleen, left kidney, and gallbladder). We directly compared the segmentation accuracy of the proposed method to the existing deep learning and MALF methods in a cross-validation on a multi-centre data set with 90 subjects. The proposed method yielded significantly higher Dice scores for all organs and lower mean absolute distances for most organs, including Dice scores of 0.78 versus 0.71, 0.74, and 0.74 for the pancreas, 0.90 versus 0.85, 0.87, and 0.83 for the stomach, and 0.76 versus 0.68, 0.69, and 0.66 for the esophagus. We conclude that the deep-learning-based segmentation represents a registration-free method for multi-organ abdominal CT segmentation whose accuracy can surpass current methods, potentially supporting image-guided navigation in gastrointestinal endoscopy procedures.

在计算机断层扫描（CT）图像上自动分割腹部解剖结构可以支持诊断、治疗计划制定和治疗实施流程。使用统计模型和多图谱标签融合（MALF）的分割方法需要个体间图像配准，这对腹部图像来说具有挑战性，而无配准的替代方法在大多数腹部器官上尚未达到更高精度。我们提出了一种免配准的深度学习分割算法，用于与内镜下胰腺和胆道手术导航相关的八个器官，包括胰腺、胃肠道（食管、胃和十二指肠）以及周围器官（肝脏、脾脏、左肾和胆囊）。我们在一个包含90名受试者的多中心数据集中，通过交叉验证直接将所提方法与现有深度学习和MALF方法的分割精度进行了比较。所提方法在所有器官上都获得了显著更高的Dice分数，并且在大多数器官上获得了更低的平均绝对距离，包括胰腺的Dice分数为0.78对比0.71、0.74和0.74，胃为0.90对比0.85、0.87和0.83，食管为0.76对比0.68、0.69和0.66。我们得出结论，基于深度学习的分割代表了一种用于多器官腹部CT分割的免配准方法，其精度可以超越当前方法，有可能支持胃肠道内镜手术中的图像引导导航。

The success of deep convolutional neural networks (NNs) on image classification and recognition tasks has led to new applications in very diversified contexts, including the field of medical imaging. In this paper, we investigate and propose NN architectures for automated multiclass segmentation of anatomical organs in chest radiographs (CXRs), namely for lungs, clavicles, and heart. We address se...

深度卷积神经网络在图像分类和识别任务上的成功导致了其在非常多样化的环境中的新应用，包括医学成像领域。在本文中，我们研究并提出了用于胸部X光片（CXR）中解剖器官自动多类分割的神经网络架构，即针对肺、锁骨和心脏。我们解决...

Segmentation of brain tumors from magnetic resonance imaging (MRI) data sets is of great importance for improved diagnosis, growth rate prediction, and treatment planning. However, automating this process is challenging due to the presence of severe partial volume effect and considerable variability in tumor structures, as well as imaging conditions, especially for the gliomas. In this paper, we i...

从磁共振成像数据集分割脑肿瘤对于改善诊断、生长率预测和治疗规划具有重要意义。然而，由于严重的部分容积效应以及肿瘤结构和成像条件的显著变异性（尤其是胶质瘤），自动化这一过程具有挑战性。本文中，我们...

Epicardial adipose tissue (EAT) is a visceral fat deposit related to coronary artery disease. Fully automated quantification of EAT volume in clinical routine could be a timesaving and reliable tool for cardiovascular risk assessment. We propose a new fully automated deep learning framework for EAT and thoracic adipose tissue (TAT) quantification from non-contrast coronary artery calcium computed ...

心外膜脂肪组织（EAT）是一种与冠状动脉疾病相关的内脏脂肪沉积。在临床常规中，全自动定量EAT体积可以成为心血管风险评估中节省时间且可靠的工具。我们提出了一种新的全自动深度学习框架，用于从非对比冠状动脉钙化计算机断层扫描中定量EAT和胸腔脂肪组织（TAT）。

Limited capture range, and the requirement to provide high quality initialization for optimization-based 2-D/3-D image registration methods, can significantly degrade the performance of 3-D image reconstruction and motion compensation pipelines. Challenging clinical imaging scenarios, which contain significant subject motion, such as fetal in-utero imaging, complicate the 3-D image and volume reco...

有限的捕获范围以及为基于优化的2-D/3-D图像配准方法提供高质量初始化的需求，会显著降低3-D图像重建和运动补偿管道的性能。包含显著受试者运动（如胎儿宫内成像）的具有挑战性的临床成像场景，使得3-D图像和体积重建复杂化。

Characterizing the viscoelastic properties of thin-layer tissues with micro-level thickness has long remained challenging. Recently, several micro-elastography techniques have been developed to improve the spatial resolution. However, most of these techniques have not considered the medium boundary conditions when evaluating the viscoelastic properties of thin-layer tissues such as arteries and co...

表征微米级厚度薄层组织的粘弹性特性长期以来一直具有挑战性。近年来，为了改善空间分辨率，已经发展了几种微弹性成像技术。然而，大多数这些技术在评估薄层组织（如动脉等）的粘弹性特性时没有考虑介质边界条件。

The very high frame rate afforded by ultrafast ultrasound, combined with microbubble contrast agents, opens new opportunities for imaging tissue microvasculature. However, new imaging paradigms are required to obtain superior image quality from the large amount of acquired data while allowing real-time implementation. In this paper, we report a technique–acoustic sub-aperture processing (ASAP)–cap...

超快超声提供的高帧率，结合微泡造影剂，为组织微血管成像开辟了新的机遇。然而，需要新的成像范式来从大量采集数据中获得卓越的图像质量，同时实现实时处理。在本文中，我们报告了一种技术——声学子孔径处理（ASAP）——...

Magnetic particle imaging (MPI) is a novel imaging modality with important potential applications, such as angiography, stem cell tracking, and cancer imaging. Recently, there have been efforts to increase the functionality of MPI via multi-color imaging methods that can distinguish the responses of different nanoparticles, or nanoparticles in different environmental conditions. The proposed techn...

磁粒子成像（MPI）是一种新颖的成像模态，具有重要的潜在应用，例如血管造影、干细胞追踪和癌症成像。最近，人们努力通过多色成像方法来增加MPI的功能，这些方法可以区分不同纳米颗粒或不同环境条件下纳米颗粒的响应。所提出的技术...

Reducing the number of false discoveries is presently one of the most pressing issues in the life sciences. It is of especially great importance for many applications in neuroimaging and genomics, where data sets are typically high-dimensional, which means that the number of explanatory variables exceeds the sample size. The false discovery rate (FDR) is a criterion that can be employed to address...

减少假发现的数量目前是生命科学中最紧迫的问题之一。对于神经影像学和基因组学中的许多应用尤其重要，这些领域的数据集通常是高维的，这意味着解释变量的数量超过样本量。错误发现率（FDR）是可以用来解决这一问题的标准...

Isotropic three-dimensional (3D) acquisition is a challenging task in magnetic resonance imaging (MRI). Particularly in cardiac MRI, due to hardware and time limitations, current 3D acquisitions are limited by low-resolution, especially in the through-plane direction, leading to poor image quality in that dimension. To overcome this problem, super-resolution (SR) techniques have been proposed to r...

各向同性三维(3D)采集是磁共振成像(MRI)中的一项挑战性任务。特别是在心脏MRI中，由于硬件和时间限制，当前的3D采集受限于低分辨率，尤其是在穿平面方向上，导致该维度的图像质量较差。为了克服这个问题，超分辨率(SR)技术已被提出，以...

The O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation and isocitrate dehydrogenase 1 (IDH1) mutation in high-grade gliomas (HGG) have proven to be the two important molecular indicators associated with better prognosis. Traditionally, the statuses of MGMT and IDH1 are obtained via surgical biopsy, which has limited their wider clinical implementation. Accurate presurgical predicti...

高级别胶质瘤（HGG）中的O6-甲基鸟嘌呤-DNA甲基转移酶（MGMT）启动子甲基化和异柠檬酸脱氢酶1（IDH1）突变已被证明是与较好预后相关的两个重要分子指标。传统上，MGMT和IDH1的状态通过外科活检获得，这限制了它们在更广泛临床中的应用。准确的术前预测...

Compared with conventional computed tomography (CT), dual-energy CT (DECT) provides better material differentiation but requires projection data acquired with two different effective x-ray spectra, limiting DECT applications to specialized scanners. We propose a hardware-based method, known as PM-DECT, which utilizes primary beam modulation to enable single-scan DECT on a conventional CT scanner. ...

与传统的计算机断层扫描（CT）相比，双能CT（DECT）提供了更好的材料区分能力，但需要利用两种不同的有效X射线能谱获取投影数据，这限制了DECT在专用扫描仪上的应用。我们提出了一种基于硬件的方法，称为PM-DECT，它利用初级束调制在常规CT扫描仪上实现单次扫描DECT。...

We present a novel technique for real-time deformable registration of 3-D to 2.5-D transrectal ultrasound (TRUS) images for image-guided, robot-assisted laparoscopic radical prostatectomy (RALRP). For RALRP, a pre-operatively acquired 3-D TRUS image is registered to thin-volumes comprised of consecutive intra-operative 2-D TRUS images, where the optimal transformation is found using a gradient des...

我们提出了一种新颖的技术，用于实时可变形配准三维到二点五维经直肠超声（TRUS）图像，以应用于图像引导的机器人辅助腹腔镜根治性前列腺切除术（RALRP）。对于RALRP，将术前获取的三维TRUS图像与由连续的术中二维TRUS图像组成的薄层体积进行配准，通过梯度下降法找到最佳变换。

Recent advances in optical coherence tomography (OCT) lead to the development of OCT angiography to provide additional helpful information for diagnosis of diseases like basal cell carcinoma. In this paper, we investigate how to extract blood vessels of human skin from full-field OCT (FF-OCT) data using the robust principal component analysis (RPCA) technique. Specifically, we propose a short-time...

光学相干断层扫描（OCT）的最新进展推动了OCT血管造影的发展，为基底细胞癌等疾病的诊断提供了额外的有用信息。本文研究如何使用鲁棒主成分分析（RPCA）技术从全视野OCT（FF-OCT）数据中提取人体皮肤的血管。具体来说，我们提出了一种短时...

Microwave radar imaging is promising as a complementary medical imaging modality. However, the unique nature of the images means interpretation can be difficult. As a result, it is important to understand the sources of image differences, and how much variability is inherent in the imaging system itself. To address this issue, we compare the effectiveness of six different measures of image similar...

微波雷达成像作为一种互补的医学成像模态具有前景。然而，图像的特殊性使得解释变得困难。因此，了解图像差异的来源以及成像系统本身固有的变异性至关重要。为了解决这个问题，我们比较了六种不同图像相似度度量的有效性...

In this paper, we analyze how stabilizing the variance of intensity-dependent quantum noise in digital mammograms can significantly improve the computerized detection of microcalcifications (MCs). These lesions appear on mammograms as tiny deposits of calcium smaller than 20 pixels in diameter. At this scale, high frequency image noise is dominated by quantum noise, which in raw mammograms can be ...

在本文中，我们分析了稳定数字乳腺X线影像中强度相关量子噪声的方差如何显著改善微钙化的计算机检测。这些病变在乳腺X线影像上表现为直径小于20像素的微小钙沉积。在此尺度下，高频图像噪声主要由量子噪声主导，在原始乳腺X线影像中可能...

Charge sharing, scatter, and fluorescence events in a photon counting detector can result in counting of a single incident photon in multiple neighboring pixels, each at a fraction of the true energy. This causes energy distortion and correlation of data across energy bins in neighboring pixels (spatio-energy correlation), with the severity depending on the detector pixel size and detector materia...

光子计数探测器中的电荷共享、散射和荧光事件可能导致单个入射光子被多个相邻像素计数，每个像素记录的能量仅为真实能量的一部分。这会导致能量失真以及相邻像素间能箱数据的相关性（空间-能量相关性），其严重程度取决于探测器像素尺寸和探测器材料...

Passive monitoring of the thermal noise variances of the channels of a receive array was shown to reveal respiratory motion of the underlying anatomy, a so called “noise navigator”. There is, however, an inevitable trade off between the accuracy and temporal resolution of the noise navigator due to its passive nature. A temporal filter has to be added to the noise navigator to accurately reveal re...

被动监测接收阵列通道的热噪声方差已被证明可以揭示底层解剖结构的呼吸运动，即所谓的“噪声导航器”。然而，由于噪声导航器的被动性质，其准确性和时间分辨率之间存在着不可避免的权衡。为了准确揭示呼吸运动，必须在噪声导航器中添加时间滤波器...

High peak RF amplitude and excessive specific absorption rate (SAR) are two critical concerns for hardware implementation and patient safety in scientific and clinical research for high field MRI using parallel transmissions (pTX). In this paper, we introduce a squeezing strategy to reduce peak RF amplitude and integrated RF power via direct reshaping of the k-space trajectory. In the existing pea...

高峰值射频幅度和过度的比吸收率（SAR）是科学和临床研究中高场MRI使用并行传输（pTX）时硬件实现和患者安全两个关键问题。本文介绍了一种通过直接重塑k空间轨迹来降低峰值射频幅度和积分射频功率的压缩策略。在现有的pea...

In the above paper [1], there are typos in Algorithm 1 table. The correct version of Algorithm 1 is given below.

在上述论文[1]中，算法1表格中存在拼写错误。下面给出算法1的正确版本。

Presents information on the searsch for a new Editor-in-Chief for this publication.

提供关于为本刊寻找新任主编的信息。

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

列出本期出版物的编委会、理事会、现任工作人员、委员会成员和/或学会编辑。

Presents the table of contents for this issue of the publication.

呈现本期出版物的目录。

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.

这些说明为准备本刊论文提供指导。为在本期刊上发表文章的作者提供信息。