高能数据缺失下的双能CT重建算法实验研究

随着全球恐怖主义事件数量的逐年递增,公共安全问题越来越受到各国的重视,对安检系统的需求也越来越高。具有高精度物质识别特性的双能CT检测系统一直被认为是防范恐怖事件发生的最有效工具之一。但目前最典型的伪双能CT成像系统是由高低能量不同的两层全采样探测器单元组成。大量探测器单元的使用大大提升了系统成本,阻碍了大规模商用。2013年,我们提出了一种基于压缩感知理论的双能CT不完备数据重建算法,该算法仅利用少数高能探测器缺失数据即可实现图像质量相当的重建过程,模拟实验初步验证了算法的有效性。本文进一步使用在双能CT物品机上采集的真实数据验证算法的有效性。实验结果表明,在确保双能CT重建图像质量的前提下,使用基于压缩感知理论的双能CT不完备数据重建算法可以将双能CT探测器成本降低25％。     

双能DR物质识别算法在CT成像系统中的应用

本文介绍一种适用于计算机断层成像（CT）的双能透视（DR）物质识别算法，此算法基于单能CT重建图像，通过对CT图像的分割及对断层几何信息的提取，分块重建材料有效原子序数及电子密度的分布。结合各种扫描轨迹的CT成像系统，可以实现有效的物质材料识别。同时，对比于传统的双能CT方法，本方法结合单能CT重建图像，改善了双能DR识别效果，能够实现较为精确的物质识别，在安全检查等应用领域有着现实意义。     

基于光线投射的锥束CT正投影算法研究

计算机断层成像（computed tomography,CT）作为一种现代成像技术已经被广泛应用于医学诊断、工业无损检测等领域。在研究CT重建算法的过程中,正投影模拟数据是必不可少的一部分。本文提出一种基于光线投射算法的圆轨迹锥束扫描模式下的正投影算法,并结合CUDA（compute unified device architecture,统一计算设备架构）技术,实现了GPU（graphics processing unit,图形处理器）加速正投影计算。通过与传统的正投影算法相比,本文算法在投影图像质量上有一定的提高,并具有更高的计算效率。     

首都师范大学检测成像实验室CT研究进展

CT检测成像技术包括数据采集、图像重建、图像应用三个层面。本文简要介绍了近年来首都师范大学检测成像实验室在这三个层面技术研究方面所取得的进展。具体包括多种新的扫描模式和相应重建算法、X射线能量谱的研究、基于GPU的多种解析重建算法和迭代重建算法的加速实现方法、多种伪影形成机理的研究及有效的伪影校正方法、基于GPU实现的体绘制算法、基于这些研究成果的算法平台和软件研发以及成果推广应用情况等。本文目的在于与本领域专家交流相关问题的国内外研究状况及本实验室的研究进展,促进研究的进一步深入。     

基于全变分与交替保边扩散平滑的稀疏角度CT重建算法

通过全变分(TV)正则化重建CT图像,虽然在一定程度上可以有效地提高图像重建质量,但在图像边缘存在过度平滑的现象。因此,本文基于TV算法,结合保边延拓和平滑算法(AEDS)的保边性能,提出一种用于稀疏图像重建的双约束迭代CT重建算法。通过使用TV算法和AEDS算法,对重建图像进行稀疏正则化,以更好地抑制噪声,达到边缘保护的效果。经实验结果表明,与其他算法相比,所提算法在抑制噪声的同时,保留了图像更多细节及边缘结构,提高了重建图像质量。     

有限角CT成像研究进展

有限角CT成像在工业和医学CT成像中都有重要的应用需求,但由于获得的投影数据不完备,有限角CT成像问题高度病态,以致传统算法重建的CT图像中出现严重的有限角伪影,从而影响CT图像的阅片和判读。为了解决该问题,国内外学者对有限角CT成像理论和算法做了大量研究。本文首先简要介绍了有限角CT图像伪影的特点;然后重点综述了有限角CT图像重建算法的研究进展,包括作者所在团队所做的相关研究和探索;最后概述了目前存在的问题以及对进一步研究的展望。     

面向CT成像的深度重建算法研究进展

随着计算机断层扫描(Computed Tomography, CT)技术的发展与广泛应用,其重建算法得到了长足的发展。近年来,基于数据驱动的深度学习技术与CT图像重建结合的趋势愈加明显,深度学习应用于影像重建在实验环境中取得了显著的重建效果。本文以CT成像原理、重建技术发展以及存在问题为切入点。首先,围绕深度学习的有监督和无监督学习策略,将两类基于深度学习的重建算法原理与目前国内外研究进展进行结合介绍。主要包括有监督学习对传统解析迭代方法重建过程的网络实现与优化,以及无监督学习中自监督学习和生成模型类重建原理方法。其次,介绍了一些常用的基于像素、区域结构细节、语义特征等层面的损失函数,并对它们的优缺点进行了分析。最后,本文对深度重建领域仍存在的一些问题进行了总结,并介绍了一些新的学习型重建策略。     

实时定位轨迹工业CT系统研究

计算机断层成像（CT）在扫描时需要高精度的机械运动以保证重建图像的质量。在工业CT的应用中,如果被检测物体体型较大,高精度的机械运动系统将会难以实现。本文提出了一种基于实时定位系统的工业CT实现方案,以提高大型工业CT系统的适用性。该方案包括视觉定位系统的实现、定位系统位置的选择与性能评估,以及结合定位信息的图像重建方法。基于以上方案,本文以多段直线轨迹扫描为例,模拟了扫描过程中可能出现的移动和定位的误差,并结合模拟扫描数据进行重建。重建结果表明该方法可以减少机械系统不精确所造成的影响,在一定程度上提高了图像的质量。     

能谱CT图像重建算法研究

能谱CT所获取的是多个能谱(或能段)的X射线穿过被测物体的扫描数据。与传统CT扫描数据相比,这些数据中包含着更多的被测物体信息。基于基材料分解算法,能谱CT可重建被测物体的多个基材料图像,以及由基图像线性组合表示的虚拟单能图像,并由此进行物体成分识别和定量化分析。近年来,能谱CT成像的相关理论、技术、器件和系统都在快速发展,其应用领域也在日益扩大。本文在介绍能谱CT的数据采集模式、基材料分解数学模型的基础上,综述基于基材料分解的能谱CT图像重建算法的分类及各类算法的优缺点和适用性等,并探讨需要进一步研究的相关问题。     

锥束覆盖方法的并行实现及性能分析

三维螺旋锥束CT重建算法的快速实现是CT理论与实际应用中关注的焦点。本文基于锥束覆盖方法[1]对Katsevich精确反演公式设计了并行算法并给出了算法的并行性能分析。从本文的结果可以看出,该算法是解决三维螺旋锥束CT的重建算法时效性的一个可行途径。     

Compressed sensing for reduction of noise and artefacts in direct PET image reconstruction

AimImage reconstruction in positron emission tomography (PET) can be performed using either direct or iterative methods. Direct reconstruction methods need a short reconstruction time. However, for data containing few counts, they often result in poor visual images with high noise and reconstruction artefacts. Iterative reconstruction methods such as ordered subset expectation maximization (OSEM) can lead to overestimation of activity in cold regions distorting quantitative analysis. The present work investigates the possibilities to reduce noise and reconstruction artefacts of direct reconstruction methods using compressed sensing (CS).Materials and methodsRaw data are generated either using Monte Carlo simulations using GATE or are taken from PET measurements with a Siemens Inveon small-animal PET scanner. The fully sampled dataset was reconstructed using filtered backprojection (FBP) and reduced in Fourier space by multiplication with an incoherently undersampled sampling pattern, followed by an additional reconstruction with CS. Different sampling patterns are used and an average of the reconstructions is taken. The images are compared to the results of an OSEM reconstruction and quantified using signal-to-noise ratio (SNR).ResultsThe application of the proposed CS post-processing technique clearly improves the image contrast. Dependent on the undersampling factor, noise and artefacts are reduced resulting in an SNR that is increased up to 3.4-fold. For short acquisition times with low count statistics the SNR of the CS reconstructed image exceeds the SNR of the OSEM reconstruction.ConclusionEspecially for low count data, the proposed CS-based post-processing method applied to FBP reconstructed PET images enhances the image quality significantly.     

基于不可分离MRA的小波图像重建

本文提出了一种基于不可分离MRA的小波重建算法。算法将投影数据进行二通道的小波分解，在分解抽样中，使用不同的抽样方法。算法结果，相比通常所使用的基于可分离MRA的小波重建算法基本相同的局部重建特性，重建质量和运算速度都优于后者。     

一种实用的基于GPU的Katsevich算法的实现

Katseivch算法是精确地解决锥束螺旋CT“长物体”问题的滤波反投影（FBP）形式的CT重建算法,不过它依然是非常耗时的,实际应用中必须考虑如何加速的问题。本文给出了一个使用通用显卡（GPU）对该算法进行并行加速的方法。同已有的方法相比较,几乎所有的计算都在GPU上完成,并且重建时所使用的积分范围是由PI线决定的,并且给出了算法所需要的精确地显存大小,10次数也被最大可能地降低。本文使用了标准数值模型对方法的速度、准确性和稳定性进行了验证。     

Progress in SPECT/CT imaging of prostate cancer

Prostate cancer is the most common type of cancer (other than skin cancer) among men in the United States. Although prostate cancer is one of the few cancers that grow so slowly that it may never threaten the lives of some patients, it can be lethal once metastasized. Indium-111 capromab pendetide (ProstaScint, Cytogen Corporation, Princeton, NJ) imaging is indicated for staging and recurrence detection of the disease, and is particularly useful to determine whether or not the disease has spread to distant metastatic sites. However, the interpretation of 111In-capromab pendetide is challenging without correlated structural information mostly because the radiopharmaceutical demonstrates nonspecific uptake in the normal vasculature, bowel, bone marrow, and the prostate gland. We developed an improved method of imaging and localizing 111In-Capromab pendetide using a SPECT/CT imaging system. The specific goals included: i) development and application of a novel iterative SPECT reconstruction algorithm that utilizes a priori information from coregistered CT; and ii) assessment of clinical impact of adding SPECT/CT for prostate cancer imaging with capromab pendetide utilizing the standard and novel reconstruction techniques. Patient imaging studies with capromab pendetide were performed from 1999 to 2004 using two different SPECT/CT scanners, a prototype SPECT/CT system and a commercial SPECT/CT system (Discovery VH, GE Healthcare, Waukesha, WI). SPECT projection data from both systems were reconstructed using an experimental iterative algorithm that compensates for both photon attenuation and collimator blurring. In addition, the data obtained from the commercial system were reconstructed with attenuation correction using an OSEM reconstruction supplied by the camera manufacturer for routine clinical interpretation. For 12 sets of patient data, SPECT images reconstructed using the experimental algorithm were interpreted separately and compared with interpretation of images obtained using the standard reconstruction technique. The experimental reconstruction algorithm improved spatial resolution, reduced streak artifacts, and yielded a better correlation with anatomic details of CT in comparison to conventional reconstruction methods (e.g., filtered back-projection or OSEM with attenuation correction only). Images produced with the experimental algorithm produced a subjective improvement in the confidence of interpretation for 11 of 12 studies. There were also changes in interpretations for 4 of 12 studies although the changes were not sufficient to alter prognosis or the patient treatment plan.     

Ultra-fast digital tomosynthesis reconstruction using general-purpose GPU programming for image-guided radiation therapy

The purpose of this work is to demonstrate an ultra-fast reconstruction technique for digital tomosynthesis (DTS) imaging based on the algorithm proposed by Feldkamp, Davis, and Kress (FDK) using standard general-purpose graphics processing unit (GPGPU) programming interface. To this end, the FDK-based DTS algorithm was programmed "in-house" with C language with utilization of 1) GPU and 2) central processing unit (CPU) cards. The GPU card consisted of 480 processing cores (2 x 240 dual chip) with 1,242 MHz processing clock speed and 1,792 MB memory space. In terms of CPU hardware, we used 2.68 GHz clock speed, 12.0 GB DDR3 RAM, on a 64-bit OS. The performance of proposed algorithm was tested on twenty-five patient cases (5 lung, 5 liver, 10 prostate, and 5 head-and-neck) scanned either with a full-fan or half-fan mode on our cone-beam computed tomography (CBCT) system. For the full-fan scans, the projections from 157.5°-202.5° (45°-scan) were used to reconstruct coronal DTS slices, whereas for the half-fan scans, the projections from both 157.5°-202.5° and 337.5°-22.5° (2 x 45°-scan) were used to reconstruct larger FOV coronal DTS slices. For this study, we chose 45°-scan angle that contained ~80 projections for the full-fan and ~160 projections with 2 x 45°-scan angle for the half-fan mode, each with 1024 x 768 pixels with 32-bit precision. Absolute pixel value differences, profiles, and contrast-to-noise ratio (CNR) calculations were performed to compare and evaluate the images reconstructed using GPU- and CPU-based implementations. The time dependence on the reconstruction volume was also tested with (512 x 512) x 16, 32, 64, 128, and 256 slices. In the end, the GPU-based implementation achieved, at most, 1.3 and 2.5 seconds to complete full reconstruction of 512 x 512 x 256 volume, for the full-fan and half-fan modes, respectively. In turn, this meant that our implementation can process > 13 projections-per-second (pps) and > 18 pps for the full-fan and half-fan modes, respectively. Since commercial CBCT system nominally acquires 11 pps (with 1 gantry-revolution-per-minute), our GPU-based implementation is sufficient to handle the incoming projections data as they are acquired and reconstruct the entire volume immediately after completing the scan. In addition, on increasing the number of slices (hence volume) to be reconstructed from 16 to 256, only minimal increases in reconstruction time were observed for the GPU-based implementation where from 0.73 to 1.27 seconds and 1.42 to 2.47 seconds increase were observed for the full-fan and half-fan modes, respectively. This resulted in speed improvement of up to 87 times compared with the CPU-based implementation (for 256 slices case), with visually identical images and small pixel-value discrepancies (< 6.3%), and CNR differences (< 2.3%). With this achievement, we have shown that time allocation for DTS image reconstruction is virtually eliminated and that clinical implementation of this approach has become quite appealing. In addition, with the speed achievement, further image processing and real-time applications that was prohibited prior due to time restrictions can now be tempered with.     

DART-TV：高精度离散断层图像重建算法

本文提出了一种基于离散代数迭代（DART）和全变差（TV）最小化的高精度图像重建算法,即DART．TV。该算法适用于工业CT辅助制造中对于单一材料物体的尺寸检测,特别是在物体对某些角度无法被穿透的情况。传统的CT重建算法如FBP或ART无法有效处理这类数据缺失的病态问题,重建图像分辨率差。本文提出的算法的核心思想是：（1）利用DART的结果限制重建物体的支撑域,改善问题的病态性;（2）迭代过程中施加TV约束,以抑制噪声;（3）每次迭代后自动更新支撑域,不断逼近真实解,使得图像边缘更加清晰。初步的模拟结果和实验结果显示,DART-TV算法在有限角情况下可以得到更精确的重建图像边缘,并且该算法对于投影噪声和灰度值估计误差有更好的鲁棒性,可以应用于实际工程。     

Reconstruction of 3D regions-of-interest from data in reduced helical cone-beam scans

The sufficiency conditions are derived for exact image reconstruction of a 3D ROI from projections acquired with a reduced helical scan over an angular range considerably smaller than that required by image reconstruction in, e.g., the conventional long object problem, for which the scanned angular range is often more than 2pi. ROI reconstruction is investigated by a recently developed filtered-backprojection algorithm that can make use of data acquired with a reduced helical scan. Preliminary numerical studies demonstrate and validate the ROI reconstruction. This work may have significant practical implications because a reduced scan in CT often translates to reduced motion artifacts and reduced radiation dose delivered to the subject.