International Journal of Biomedical Imaging最新文献

英文中文

An Analytical Approach for Fast Recovery of the LSI Properties in Magnetic Particle Imaging 磁颗粒成像中快速恢复LSI性能的分析方法

IF 7.6 Q2 ENGINEERING, BIOMEDICAL

International Journal of Biomedical Imaging

Pub Date : 2016-10-01 DOI: 10.1155/2016/6120713

H. Jabbari, Jungwon Yoon

Linearity and shift invariance (LSI) characteristics of magnetic particle imaging (MPI) are important properties for quantitative medical diagnosis applications. The MPI image equations have been theoretically shown to exhibit LSI; however, in practice, the necessary filtering action removes the first harmonic information, which destroys the LSI characteristics. This lost information can be constant in the x-space reconstruction method. Available recovery algorithms, which are based on signal matching of multiple partial field of views (pFOVs), require much processing time and a priori information at the start of imaging. In this paper, a fast analytical recovery algorithm is proposed to restore the LSI properties of the x-space MPI images, representable as an image of discrete concentrations of magnetic material. The method utilizes the one-dimensional (1D) x-space imaging kernel and properties of the image and lost image equations. The approach does not require overlapping of pFOVs, and its complexity depends only on a small-sized system of linear equations; therefore, it can reduce the processing time. Moreover, the algorithm only needs a priori information which can be obtained at one imaging process. Considering different particle distributions, several simulations are conducted, and results of 1D and 2D imaging demonstrate the effectiveness of the proposed approach.

磁颗粒成像(MPI)的线性和平移不变性(LSI)特性是定量医学诊断应用的重要特性。MPI图像方程已经从理论上证明了LSI的存在;然而，在实践中，必要的滤波动作去除了第一谐波信息，这破坏了LSI的特性。这种丢失的信息在x空间重建方法中可以是常数。现有的恢复算法是基于多个部分视场(pfov)的信号匹配，需要大量的处理时间和成像开始时的先验信息。本文提出了一种快速解析恢复算法，用于恢复x空间MPI图像的LSI特性，该图像可表示为磁性材料离散浓度的图像。该方法利用一维(1D) x空间成像核以及图像和丢失图像方程的性质。该方法不需要pfov的重叠，其复杂性仅取决于一个小尺寸的线性方程组;因此，可以减少处理时间。此外，该算法只需要一次成像即可获得的先验信息。在不同颗粒分布的情况下，进行了多次模拟，一维和二维成像结果验证了该方法的有效性。

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引用次数: 6

IF 7.6 Q2 ENGINEERING, BIOMEDICAL

International Journal of Biomedical Imaging

Pub Date : 2016-09-01 DOI: 10.1155/2016/7570406

J. Klock, E. Iuanow, Bilal H. Malik, N. Obuchowski, J. Wiskin, M. Lenox

Objectives. This study presents correlations between cross-sectional anatomy of human female breasts and Quantitative Transmission (QT) Ultrasound, does discriminate classifier analysis to validate the speed of sound correlations, and does a visual grading analysis comparing QT Ultrasound with mammography. Materials and Methods. Human cadaver breasts were imaged using QT Ultrasound, sectioned, and photographed. Biopsies confirmed microanatomy and areas were correlated with QT Ultrasound images. Measurements were taken in live subjects from QT Ultrasound images and values of speed of sound for each identified anatomical structure were plotted. Finally, a visual grading analysis was performed on images to determine whether radiologists' confidence in identifying breast structures with mammography (XRM) is comparable to QT Ultrasound. Results. QT Ultrasound identified all major anatomical features of the breast, and speed of sound calculations showed specific values for different breast tissues. Using linear discriminant analysis overall accuracy is 91.4%. Using visual grading analysis readers scored the image quality on QT Ultrasound as better than on XRM in 69%–90% of breasts for specific tissues. Conclusions. QT Ultrasound provides accurate anatomic information and high tissue specificity using speed of sound information. Quantitative Transmission Ultrasound can distinguish different types of breast tissue with high resolution and accuracy.

目标。本研究提出了人类女性乳房横断面解剖与定量透射(QT)超声之间的相关性，进行了判别分类器分析以验证声速相关性，并对QT超声与乳房x线摄影进行了视觉分级分析。材料与方法。用QT超声对尸体乳房进行成像、切片和拍照。活检证实显微解剖和区域与QT超声图像相关。通过QT超声图像对活体受试者进行测量，并绘制出每个确定解剖结构的声速值。最后，对图像进行视觉分级分析，以确定放射科医生用乳房x光检查(XRM)识别乳房结构的信心是否与QT超声相当。结果。QT超声识别了乳房的所有主要解剖特征，声速计算显示了不同乳房组织的特定值。采用线性判别分析，总体准确率为91.4%。使用视觉分级分析，读者在69%-90%的乳房特定组织中对QT超声的图像质量评分优于XRM。结论。QT超声提供准确的解剖信息和高组织特异性利用声音信息的速度。定量透射超声可以区分不同类型的乳腺组织，具有较高的分辨率和准确性。

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引用次数: 14

Retinal Fundus Image Enhancement Using the Normalized Convolution and Noise Removing 基于归一化卷积和去噪的视网膜眼底图像增强

IF 7.6 Q2 ENGINEERING, BIOMEDICAL

International Journal of Biomedical Imaging

Pub Date : 2016-09-01 DOI: 10.1155/2016/5075612

Peishan Dai, Hanwei Sheng, Jianmei Zhang, Ling Li, Jing Wu, Min Fan

Retinal fundus image plays an important role in the diagnosis of retinal related diseases. The detailed information of the retinal fundus image such as small vessels, microaneurysms, and exudates may be in low contrast, and retinal image enhancement usually gives help to analyze diseases related to retinal fundus image. Current image enhancement methods may lead to artificial boundaries, abrupt changes in color levels, and the loss of image detail. In order to avoid these side effects, a new retinal fundus image enhancement method is proposed. First, the original retinal fundus image was processed by the normalized convolution algorithm with a domain transform to obtain an image with the basic information of the background. Then, the image with the basic information of the background was fused with the original retinal fundus image to obtain an enhanced fundus image. Lastly, the fused image was denoised by a two-stage denoising method including the fourth order PDEs and the relaxed median filter. The retinal image databases, including the DRIVE database, the STARE database, and the DIARETDB1 database, were used to evaluate image enhancement effects. The results show that the method can enhance the retinal fundus image prominently. And, different from some other fundus image enhancement methods, the proposed method can directly enhance color images.

视网膜眼底图像在视网膜相关疾病的诊断中具有重要作用。视网膜眼底图像的细节信息如小血管、微动脉瘤、渗出物等可能对比度较低，视网膜图像增强通常有助于分析与视网膜眼底图像相关的疾病。目前的图像增强方法可能会导致人工边界、颜色水平的突变和图像细节的丢失。为了避免这些副作用，提出了一种新的视网膜眼底图像增强方法。首先，对原始视网膜眼底图像进行归一化卷积和域变换处理，得到具有背景基本信息的图像;然后，将具有背景基本信息的图像与原始视网膜眼底图像融合，得到增强的眼底图像。最后，采用四阶偏微分方程和松弛中值滤波两阶段去噪方法对融合后的图像进行去噪。视网膜图像数据库包括DRIVE数据库、STARE数据库和DIARETDB1数据库，用于评估图像增强效果。结果表明，该方法能显著增强视网膜眼底图像。与其他眼底图像增强方法不同的是，该方法可以直接增强彩色图像。

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引用次数: 54

Detection of Cardiac Function Abnormality from MRI Images Using Normalized Wall Thickness Temporal Patterns 利用归一化壁厚时间模式从MRI图像中检测心功能异常

IF 7.6 Q2 ENGINEERING, BIOMEDICAL

International Journal of Biomedical Imaging

Pub Date : 2016-03-01 DOI: 10.1155/2016/4301087

M. Wael, El-Sayed H. Ibrahim, A. Fahmy

Purpose. To develop a method for identifying abnormal myocardial function based on studying the normalized wall motion pattern during the cardiac cycle. Methods. The temporal pattern of the normalized myocardial wall thickness is used as a feature vector to assess the cardiac wall motion abnormality. Principal component analysis is used to reduce the feature dimensionality and the maximum likelihood method is used to differentiate between normal and abnormal features. The proposed method was applied on a dataset of 27 cases from normal subjects and patients. Results. The developed method achieved 81.5%, 85%, and 88.5% accuracy for identifying abnormal contractility in the basal, midventricular, and apical slices, respectively. Conclusions. A novel feature vector, namely, the normalized wall thickness, has been introduced for detecting myocardial regional wall motion abnormality. The proposed method provides assessment of the regional myocardial contractility for each cardiac segment and slice; therefore, it could be a valuable tool for automatic and fast determination of regional wall motion abnormality from conventional cine MRI images.

目的。建立一种基于心周期归一化壁运动模式的异常心肌功能识别方法。方法。将归一化心肌壁厚的时间模式作为特征向量来评估心肌壁运动异常。利用主成分分析降低特征维数，利用最大似然法区分正常与异常特征。将该方法应用于27例正常受试者和患者的数据集。结果。该方法对基底片、中脑室片和心尖片异常收缩性的识别准确率分别达到81.5%、85%和88.5%。结论。提出了一种新的特征向量，即归一化壁厚，用于检测心肌区域壁运动异常。该方法对各心脏节段和切片的局部心肌收缩力进行评估;因此，它可以成为一种有价值的工具，用于自动和快速确定区域壁运动异常从传统的电影MRI图像。

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引用次数: 3

Digital Microdroplet Ejection Technology-Based Heterogeneous Objects Prototyping 基于异构对象原型的数字微滴喷射技术

IF 7.6 Q2 ENGINEERING, BIOMEDICAL

International Journal of Biomedical Imaging

Pub Date : 2016-02-15 DOI: 10.1155/2016/5057347

Na Li, Jiaquan Yang, Chunmei Feng, Jianfei Yang, Li-ya Zhu, Aiqing Guo

An integrate fabrication framework is presented to build heterogeneous objects (HEO) using digital microdroplets injecting technology and rapid prototyping. The heterogeneous materials part design and manufacturing method in structure and material was used to change the traditional process. The net node method was used for digital modeling that can configure multimaterials in time. The relationship of material, color, and jetting nozzle was built. The main important contributions are to combine the structure, material, and visualization in one process and give the digital model for manufacture. From the given model, it is concluded that the method is effective for HEO. Using microdroplet rapid prototyping and the model given in the paper HEO could be gotten basically. The model could be used in 3D biomanufacturing.

提出了一种利用数字微滴注入技术和快速成型技术构建异构物体的集成制造框架。采用结构和材料上的异质材料零件设计制造方法，改变了传统工艺。采用网格节点法进行数字化建模，实现多材料的实时配置。建立了材料、颜色和喷嘴之间的关系。主要的贡献是将结构、材料和可视化结合在一个过程中，并给出了制造的数字模型。从给出的模型来看，该方法对HEO是有效的。利用微滴快速成型技术和本文给出的模型基本可以得到HEO。该模型可用于三维生物制造。

引用次数: 7

Parallel Digital Watermarking Process on Ultrasound Medical Images in Multicores Environment 多核环境下超声医学图像的并行数字水印处理

IF 7.6 Q2 ENGINEERING, BIOMEDICAL

International Journal of Biomedical Imaging

Pub Date : 2016-02-11 DOI: 10.1155/2016/9583727

Liang Khor Hui, Siau-Chuin Liew, J. Zain

With the advancement of technology in communication network, it facilitated digital medical images transmitted to healthcare professionals via internal network or public network (e.g., Internet), but it also exposes the transmitted digital medical images to the security threats, such as images tampering or inserting false data in the images, which may cause an inaccurate diagnosis and treatment. Medical image distortion is not to be tolerated for diagnosis purposes; thus a digital watermarking on medical image is introduced. So far most of the watermarking research has been done on single frame medical image which is impractical in the real environment. In this paper, a digital watermarking on multiframes medical images is proposed. In order to speed up multiframes watermarking processing time, a parallel watermarking processing on medical images processing by utilizing multicores technology is introduced. An experiment result has shown that elapsed time on parallel watermarking processing is much shorter than sequential watermarking processing.

随着通信网络技术的进步，数字医学图像可以通过内部网络或公共网络(如Internet)传输给医护人员，但也使传输的数字医学图像面临安全威胁，如图像被篡改或在图像中插入虚假数据，从而可能导致不准确的诊断和治疗。医学图像失真不能用于诊断目的;为此，提出了一种医学图像数字水印技术。到目前为止，大多数的水印研究都是在单帧医学图像上进行的，这在现实环境中是不现实的。提出了一种多帧医学图像的数字水印方法。为了加快多帧水印处理时间，提出了一种利用多核技术对医学图像进行并行水印处理的方法。实验结果表明，并行水印处理的运行时间比顺序水印处理要短得多。

引用次数: 12

3-D/2-D Registration of Cardiac Structures by 3-D Contrast Agent Distribution Estimation 利用三维造影剂分布估计心脏结构的三维/二维配准

IF 7.6 Q2 ENGINEERING, BIOMEDICAL

International Journal of Biomedical Imaging

Pub Date : 2016-01-22 DOI: 10.1155/2016/7690391

M. Hoffmann, Christopher Kowalewski, A. Maier, K. Kurzidim, Norbert Strobel, J. Hornegger

For augmented fluoroscopy during cardiac catheter ablation procedures, a preoperatively acquired 3-D model of the left atrium of the patient can be registered to X-ray images. Therefore the 3D-model is matched with the contrast agent based appearance of the left atrium. Commonly, only small amounts of contrast agent (CA) are used to locate the left atrium. This is why we focus on robust registration methods that work also if the structure of interest is only partially contrasted. In particular, we propose two similarity measures for CA-based registration: The first similarity measure, explicit apparent edges, focuses on edges of the patient anatomy made visible by contrast agent and can be computed quickly on the GPU. The second novel similarity measure computes a contrast agent distribution estimate (CADE) inside the 3-D model and rates its consistency with the CA seen in biplane fluoroscopic images. As the CADE computation involves a reconstruction of CA in 3-D using the CA within the fluoroscopic images, it is slower. Using a combination of both methods, our evaluation on 11 well-contrasted clinical datasets yielded an error of 7.9+/-6.3 mm over all frames. For 10 datasets with little CA, we obtained an error of 8.8+/-6.7 mm. Our new methods outperform a registration based on the projected shadow significantly (p<0.05).

对于心导管消融过程中的增强透视，术前获得的患者左心房三维模型可以与x射线图像相匹配。因此，3d模型与基于造影剂的左心房外观相匹配。通常，仅使用少量造影剂(CA)来定位左心房。这就是为什么我们专注于健壮的注册方法，如果感兴趣的结构只是部分对比，这些方法也可以工作。特别是，我们提出了两种基于ca的配准相似度度量:第一种相似度度量，显式表观边缘，侧重于通过造影剂可见的患者解剖边缘，可以在GPU上快速计算。第二种新颖的相似性度量方法计算3d模型内的造影剂分布估计(CADE)，并评估其与双翼透视图像中所见CA的一致性。由于CADE计算涉及使用透视图像中的CA在3d中重建CA，因此速度较慢。结合使用这两种方法，我们对11个对比良好的临床数据集的评估在所有框架中产生了7.9+/-6.3 mm的误差。对于10个CA较小的数据集，我们获得了8.8+/-6.7 mm的误差。我们的新方法明显优于基于投影的配准(p<0.05)。

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引用次数: 3

Insight into the Molecular Imaging of Alzheimer's Disease 洞察阿尔茨海默病的分子成像

IF 7.6 Q2 ENGINEERING, BIOMEDICAL

International Journal of Biomedical Imaging

Pub Date : 2016-01-10 DOI: 10.1155/2016/7462014

A. Arora, Neeta Bhagat

Alzheimer's disease is a complex neurodegenerative disease affecting millions of individuals worldwide. Earlier it was diagnosed only via clinical assessments and confirmed by postmortem brain histopathology. The development of validated biomarkers for Alzheimer's disease has given impetus to improve diagnostics and accelerate the development of new therapies. Functional imaging like positron emission tomography (PET), single photon emission computed tomography (SPECT), functional magnetic resonance imaging (fMRI), and proton magnetic resonance spectroscopy provides a means of detecting and characterising the regional changes in brain blood flow, metabolism, and receptor binding sites that are associated with Alzheimer's disease. Multimodal neuroimaging techniques have indicated changes in brain structure and metabolic activity, and an array of neurochemical variations that are associated with neurodegenerative diseases. Radiotracer-based PET and SPECT potentially provide sensitive, accurate methods for the early detection of disease. This paper presents a review of neuroimaging modalities like PET, SPECT, and selected imaging biomarkers/tracers used for the early diagnosis of AD. Neuroimaging with such biomarkers and tracers could achieve a much higher diagnostic accuracy for AD and related disorders in the future.

阿尔茨海默病是一种复杂的神经退行性疾病，影响着全世界数百万人。早期仅通过临床评估诊断，并通过死后脑组织病理学证实。经过验证的阿尔茨海默病生物标志物的发展推动了提高诊断和加速新疗法的发展。功能成像如正电子发射断层扫描(PET)、单光子发射计算机断层扫描(SPECT)、功能磁共振成像(fMRI)和质子磁共振波谱提供了一种检测和表征与阿尔茨海默病相关的脑血流、代谢和受体结合位点的区域变化的手段。多模态神经成像技术显示了脑结构和代谢活动的变化，以及与神经退行性疾病相关的一系列神经化学变异。基于放射性示踪剂的PET和SPECT可能为疾病的早期检测提供敏感、准确的方法。本文综述了用于AD早期诊断的神经成像方式，如PET、SPECT和选定的成像生物标志物/示踪剂。使用这些生物标记物和示踪剂的神经影像学在未来可以实现对AD和相关疾病更高的诊断准确性。

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引用次数: 19

Kinect-Based Correction of Overexposure Artifacts in Knee Imaging with C-Arm CT Systems. c臂CT系统膝关节成像中过度曝光伪影的运动学校正。

IF 7.6 Q2 ENGINEERING, BIOMEDICAL

International Journal of Biomedical Imaging

Pub Date : 2016-01-01 Epub Date: 2016-07-19 DOI: 10.1155/2016/2502486

Johannes Rausch, Andreas Maier, Rebecca Fahrig, Jang-Hwan Choi, Waldo Hinshaw, Frank Schebesch, Sven Haase, Jakob Wasza, Joachim Hornegger, Christian Riess

Objective. To demonstrate a novel approach of compensating overexposure artifacts in CT scans of the knees without attaching any supporting appliances to the patient. C-Arm CT systems offer the opportunity to perform weight-bearing knee scans on standing patients to diagnose diseases like osteoarthritis. However, one serious issue is overexposure of the detector in regions close to the patella, which can not be tackled with common techniques. Methods. A Kinect camera is used to algorithmically remove overexposure artifacts close to the knee surface. Overexposed near-surface knee regions are corrected by extrapolating the absorption values from more reliable projection data. To achieve this, we develop a cross-calibration procedure to transform surface points from the Kinect to CT voxel coordinates. Results. Artifacts at both knee phantoms are reduced significantly in the reconstructed data and a major part of the truncated regions is restored. Conclusion. The results emphasize the feasibility of the proposed approach. The accuracy of the cross-calibration procedure can be increased to further improve correction results. Significance. The correction method can be extended to a multi-Kinect setup for use in real-world scenarios. Using depth cameras does not require prior scans and offers the possibility of a temporally synchronized correction of overexposure artifacts. To achieve this, we develop a cross-calibration procedure to transform surface points from the Kinect to CT voxel coordinates.

目标。演示一种补偿膝关节CT扫描中过度暴露伪影的新方法，而无需在患者身上附加任何支持装置。c臂CT系统提供了对站立患者进行负重膝盖扫描以诊断骨关节炎等疾病的机会。然而，一个严重的问题是探测器在靠近髌骨的区域过度曝光，这是普通技术无法解决的。方法。Kinect摄像头用于通过算法去除靠近膝盖表面的过度曝光伪影。通过从更可靠的投影数据外推吸收值来纠正过度暴露的近地表膝盖区域。为了实现这一点，我们开发了一个交叉校准程序，将Kinect的表面点转换为CT体素坐标。结果。在重建数据中，两个膝关节的伪影明显减少，大部分被截断的区域得以恢复。结论。研究结果强调了该方法的可行性。可以提高交叉校准过程的精度，进一步改善校正结果。的意义。校正方法可以扩展到在现实场景中使用的多kinect设置。使用深度相机不需要事先扫描，并提供了暂时同步校正过度曝光伪影的可能性。为了实现这一点，我们开发了一个交叉校准程序，将Kinect的表面点转换为CT体素坐标。

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引用次数: 12

Recent Advances in Microwave Imaging for Breast Cancer Detection. 用于乳腺癌检测的微波成像技术的最新进展。

IF 7.6 Q2 ENGINEERING, BIOMEDICAL

International Journal of Biomedical Imaging

Pub Date : 2016-01-01 Epub Date: 2016-12-21 DOI: 10.1155/2016/5054912

Sollip Kwon, Seungjun Lee

Breast cancer is a disease that occurs most often in female cancer patients. Early detection can significantly reduce the mortality rate. Microwave breast imaging, which is noninvasive and harmless to human, offers a promising alternative method to mammography. This paper presents a review of recent advances in microwave imaging for breast cancer detection. We conclude by introducing new research on a microwave imaging system with time-domain measurement that achieves short measurement time and low system cost. In the time-domain measurement system, scan time would take less than 1 sec, and it does not require very expensive equipment such as VNA.

乳腺癌是一种最常见于女性癌症患者的疾病。早期发现可以大大降低死亡率。微波乳腺成像是一种非侵入性且对人体无害的成像技术，它为乳房 X 线照相术提供了一种前景广阔的替代方法。本文回顾了用于乳腺癌检测的微波成像技术的最新进展。最后，我们介绍了时域测量微波成像系统的最新研究成果，该系统测量时间短、系统成本低。在时域测量系统中，扫描时间将小于 1 秒，而且不需要非常昂贵的设备，如 VNA。

引用次数: 0

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