Automated localization of implanted seeds in 3D TRUS images used for prostate brachytherapy

An algorithm has been developed in this paper to localize implanted radioactive seeds in 3D ultrasound images for a dynamic intraoperative brachytherapy procedure. Segmentation of the seeds is difficult, due to their small size in relatively low quality of transrectal ultrasound (TRUS) images. In this paper, intraoperative seed segmentation in 3D TRUS images is achieved by performing a subtraction of the image before the needle has been inserted, and the image after the seeds have been implanted. The seeds are searched in a "local" space determined by the needle position and orientation information, which are obtained from a needle segmentation algorithm. To test this approach, 3D TRUS images of the agar and chicken tissue phantoms were obtained. Within these phantoms, dummy seeds were implanted. The seed locations determined by the seed segmentation algorithm were compared with those obtained from a volumetric cone-beam flat-panel micro-CT scanner and human observers. Evaluation of the algorithm showed that the rms error in determining the seed locations using the seed segmentation algorithm was 0.98 mm in agar phantoms and 1.02 mm in chicken phantoms.     

Automated 2D-3D registration of portal images and CT data using line-segment enhancement

In prostate radiotherapy, setup errors with respect to the patient's bony anatomy can be reduced by aligning 2D megavoltage (MV) portal images acquired during treatment to a reference 3D kilovoltage (kV) CT acquired for treatment planning purposes. The purpose of this study was to evaluate a fully automated 2D-3D registration algorithm to quantify setup errors in 3D through the alignment of line-enhanced portal images and digitally reconstructed radiographs computed from the CT. The line-enhanced images were obtained by correlating the images with a filter bank of short line segments, or "sticks" at different orientations. The proposed methods were validated on (1) accurately collected gold-standard data consisting of a 3D kV cone-beam CT scan of an anthropomorphic phantom of the pelvis and 2D MV portal images in the anterior-posterior (AP) view acquired at 15 different poses and (2) a conventional 3D kV CT scan and weekly 2D MV AP portal images of a patient over 8 weeks. The mean (and standard deviation) of the absolute registration error for rotations around the right-lateral (RL), inferior-superior (IS), and posterior-anterior (PA) axes were 0.212 degree (0.214 degree), 0.055 degree (0.033 degree) and 0.041 degree (0.039 degree), respectively. The corresponding registration errors for translations along the RL, IS, and PA axes were 0.161 (0.131) mm, 0.096 (0.033) mm, and 0.612 (0.485) mm. The mean (and standard deviation) of the total registration error was 0.778 (0.543) mm. Registration on the patient images was successful in all eight cases as determined visually. The results indicate that it is feasible to automatically enhance features in MV portal images of the pelvis for use within a completely automated 2D-3D registration framework for the accurate determination of patient setup errors. They also indicate that it is feasible to estimate all six transformation parameters from a 3D CT of the pelvis and a single portal image in the AP view.     

Progressive cross-section display of 3D medical images

The paper presents a hierarchical coding algorithm for 3D medical images based upon hierarchical interpolation with radial basis function networks. By using the properties of the Kronecker product, the computation of the network parameters and the 3D image reconstruction are efficiently done in (L⁴) computation time and O(L³) storage space, when applied to 3D images of size (L×L×L). A further reduction in processing time is accomplished by using sparse matrix techniques. The salient features of the proposed coding method are that arbitrary cross-section images can be progressively displayed without reconstruction of the whole 3D image; the first image reconstruction starts as soon as the first data transmission has been completed; no expanding procedure is required in 3D image reconstruction, and the blocking effects are not apparent even in the lowest-resolution image. Experimental results using two 3D MRI images, of size (128×18×64) and with 8-bit grey levels, show that the coding performance is better than that of the 3D DCT coding by about 0.25 bits pixel⁻¹ at higher bit rates, and that the new cross-section display method synthesises the coarsest (finest) section image about six (three) times faster than the standard method that requires the whole 3D image reconstruction.     

Prostate boundary segmentation from 3D ultrasound images

Segmenting, or outlining the prostate boundary is an important task in the management of patients with prostate cancer. In this paper, an algorithm is described for semiautomatic segmentation of the prostate from 3D ultrasound images. The algorithm uses model-based initialization and mesh refinement using an efficient deformable model. Initialization requires the user to select only six points from which the outline of the prostate is estimated using shape information. The estimated outline is then automatically deformed to better fit the prostate boundary. An editing tool allows the user to edit the boundary in problematic regions and then deform the model again to improve the final results. The algorithm requires less than 1 min on a Pentium III 400 MHz PC. The accuracy of the algorithm was assessed by comparing the algorithm results, obtained from both local and global analysis, to the manual segmentations on six prostates. The local difference was mapped on the surface of the algorithm boundary to produce a visual representation. Global error analysis showed that the average difference between manual and algorithm boundaries was -0.20 +/- 0.28 mm, the average absolute difference was 1.19 +/- 0.14 mm, the average maximum difference was 7.01 +/- 1.04 mm, and the average volume difference was 7.16% +/- 3.45%. Variability in manual and algorithm segmentation was also assessed: Visual representations of local variability were generated by mapping variability on the segmentation mesh. The mean variability in manual segmentation was 0.98 mm and in algorithm segmentation was 0.63 mm and the differences of about 51.5% of the points comprising the average algorithm boundary are insignificant (P < or = 0.01) to the manual average boundary.     

A software tool to straighten curved chromosome images

A software tool for straightening curved chromosomes has been developed and integrated into the freely available image analysis application Image SXM (available via the Internet at http://reg.ssci.liv.ac.uk). This new tool straightens curvilinear objects in one simple step after minimal input from the user. The ends of a curvilinear chromosome are identified by the user using the mouse and a window is opened displaying the object as it would appear if it was straightened out. This image processing produces linear images of chromosomes with no loss of resolution or spatial calibration, making subsequent analysis significantly more straightforward.     

3D interfractional patient position verification using 2D-3D registration of orthogonal images

Reproducible positioning of the patient during fractionated external beam radiation therapy is imperative to ensure that the delivered dose distribution matches the planned one. In this paper, we expand on a 2D-3D image registration method to verify a patient's setup in three dimensions (rotations and translations) using orthogonal portal images and megavoltage digitally reconstructed radiographs (MDRRs) derived from CT data. The accuracy of 2D-3D registration was improved by employing additional image preprocessing steps and a parabolic fit to interpolate the parameter space of the cost function utilized for registration. Using a humanoid phantom, precision for registration of three-dimensional translations was found to be better than 0.5 mm (1 s.d.) for any axis when no rotations were present. Three-dimensional rotations about any axis were registered with a precision of better than 0.2 degrees (1 s.d.) when no translations were present. Combined rotations and translations of up to 4 degrees and 15 mm were registered with 0.4 degrees and 0.7 mm accuracy for each axis. The influence of setup translations on registration of rotations and vice versa was also investigated and mostly agrees with a simple geometric model. Additionally, the dependence of registration accuracy on three cost functions, angular spacing between MDRRs, pixel size, and field-of-view, was examined. Best results were achieved by mutual information using 0.5 degrees angular spacing and a 10 x 10 cm2 field-of-view with 140 x 140 pixels. Approximating patient motion as rigid transformation, the registration method is applied to two treatment plans and the patients' setup errors are determined. Their magnitude was found to be < or = 6.1 mm and < or = 2.7 degrees for any axis in all of the six fractions measured for each treatment plan.     

Automated solid models from serial section images

A new method for creating unambiguous and complete boundary representation solid models with a hybrid polygonal/nonuniform rational B spline representation was developed and tested using computed tomography scans of the wrist. Polygon surface approximation was applied to a sequence of parallel planar outlines of individual bone elements in the wrist. An automated technique for the transformation of edge contours into solid models was implemented. This was performed using a custom batch file command sequence generator coupled to a commercially available mechanical computer-aided design and engineering software system known as I-DEAS (Structural Dynamics Research Corporation, Milford, OH). This transformation software allows the use of biomedical scan slice data with a solid modeler.     

基于二维X线图像骨组织三维重建的研究进展

医学图像的三维重建是当前国内外图像处理技术研究的热点,基于二维X线图像的三维重建这一新的重建方法在骨科疾病诊疗中的实际应用,不仅能够减少患者的检查费用,检查辐射剂量,更克服了传统的三维重建方式对检查体位的限制。本文结合近年来关于应用二维X线图像进行骨组织三维重建的文献报道,对这一重建方法的重建思路变化以及重建依据的分类进行总结,着重介绍了其在长管状骨、髋膝关节以及脊柱侧凸畸形等方面的应用情况,在对困扰其实际应用的旋转角度限制、图像分割识别等问题进行分析后,认为其必将在人体各组织器官的三维重建中得到应用。     

Automated computer optimization for 3D treatment planning of breast irradiation

A software package, capable of optimizing beam energy and weight and wedge angle and orientation in conjunction with commercial treatment planning system, has been developed to effectively generate three-dimensional conformal radiation therapy (3DCRT) plans for breast irradiation with complicated dosimetry requirements. A nonlinear optimization procedure was utilized for the optimization. The study with 15 patient cases shows that the technique can reduce treatment planning time and effort significantly and can give comparable or slightly better dosimetry results. The package can also be used to optimize the beam weights of 3DCRT plans for other treatment sites.     

一种新的CT图像软组织显示方法

本文提出了一种新的软组织显示实现方案，由分割、距离变换、剥皮和体绘制四个步骤组成。在距离变换阶段，该方案采用了一种新的三维欧氏距离变换算法，在保证距离测量精度的同时缩短了运算时间。在体绘制阶段，采用了一种基于体绘制的三维数据场多表面显示方法，为缩短绘制时间它只考虑不同物质的边界体元对显示图象的贡献，并采用投影成像法对边界体元进行快速显示，提高了三维显示的质量。该方案被用于三维医学CT图像中软组织的显示。实验结果表明，该方法能够清晰地再现皮下血管、肌肉与骨骼的空间解剖关系，在临床医学领域具有重要的应用价值。     

医学图像三维重建的加速技术

利用二维切片数据重建三维结构,在医学领域有着重要的作用.在大数据量的情况下,等值面抽取的计算效率是富有挑战性的课题.本文介绍了八叉树加速算法,以及一个从轮廓线抽取三维模型的新加速算法,该算法着眼于减少对网格点的访问次数,对网格点访问一次就建立所有cube单元的索引值、所有cube棱边上的插值点等信息.最后针对相同的数据分别使用这两种加速算法和传统MC方法进行了比较.从实验结果看,这两种算法大大加速了传统的移动立方体(marching cubes)方法,特别是在大数据量时,加速效果非常明显.     

一种基于2D/3D配准的脊柱术中校正方法

背景：脊柱术前三维影像有助于诊断和治疗,术中患者体位变化将引起脊柱形态改变,致使术前影像不能反映术中实际情况,无法确保手术的顺利实施。 目的：利用脊髓手术中影像校正术前脊柱模型形态。 方法：实验提出了一种基于2D/3D配准的脊柱术中校正方法,借助数字影像重建技术完成术前X射线图像与CT体数据的2D/3D配准,进一步完成术中、术前X射线图像中独立椎段的特征匹配,利用上述配准结果实现术前脊柱CT模型的术中快速校正。 结果与结论：采用附有标记的颈椎标本进行实验,校正后可基本消除术前脊柱模型与术中形态的偏差,其误差可控制在1 mm以内,能够满足医学临床要求。     

Registration of 2D x-ray images to 3D MRI by generating pseudo-CT data

Spatial and soft tissue information provided by magnetic resonance imaging can be very valuable during image-guided procedures, where usually only real-time two-dimensional (2D) x-ray images are available. Registration of 2D x-ray images to three-dimensional (3D) magnetic resonance imaging (MRI) data, acquired prior to the procedure, can provide optimal information to guide the procedure. However, registering x-ray images to MRI data is not a trivial task because of their fundamental difference in tissue contrast. This paper presents a technique that generates pseudo-computed tomography (CT) data from multi-spectral MRI acquisitions which is sufficiently similar to real CT data to enable registration of x-ray to MRI with comparable accuracy as registration of x-ray to CT. The method is based on a k-nearest-neighbors (kNN)-regression strategy which labels voxels of MRI data with CT Hounsfield Units. The regression method uses multi-spectral MRI intensities and intensity gradients as features to discriminate between various tissue types. The efficacy of using pseudo-CT data for registration of x-ray to MRI was tested on ex vivo animal data. 2D-3D registration experiments using CT and pseudo-CT data of multiple subjects were performed with a commonly used 2D-3D registration algorithm. On average, the median target registration error for registration of two x-ray images to MRI data was approximately 1 mm larger than for x-ray to CT registration. The authors have shown that pseudo-CT data generated from multi-spectral MRI facilitate registration of MRI to x-ray images. From the experiments it could be concluded that the accuracy achieved was comparable to that of registering x-ray images to CT data.     

激光扫描多平面动态测量下颈椎椎间高度退变后椎间孔的变化

目的　激光扫描三维重建后动态测量下颈椎椎间高度退变时相应节段椎间孔的变化,为临床诊治神经根型颈椎病提供新的思路和参考。 方法 选用6具新鲜成人尸体颈椎标本,以C5/6单节段脊柱功能单位（FSU）作为研究对象。椎间盘切除后将C5/6椎间高度置于基准高度状态,激光扫描仪扫描收集该状态下C5/6 FSU的空间关系信息,再对骨性单椎体进行全面扫描,在Geomagic Studio8.0软件中再现　C5/6基准状态,并模拟6种椎间高度退变模型,即C5椎向C6椎椎体面趋于平行移动基准高度的10%、　20%、30%、40%、50%和60%。多平面动态测量方法（MPDM）分别测量椎间孔容积、中间面积、内口以及外口面积。 结果 测量数据显示随着椎间高度持续的下降,椎间孔的容积和面积逐渐减小,当椎间高度丢失基准高度30%时,椎间孔中间面积首先开始与基准状态有显著性差异（P=0.003）。 结论 激光扫描三维重建原貌再现骨性表面,是获得精确测量数据的前提;动态测量的方法较为客观准确,是测量椎间孔的理想方法;测量发现在下颈椎骨性椎间孔随着椎间高度在下降而缩小,其中间面积首先发生显著缩小,提示此处容易发生狭窄而引起临床症状。     

Segmentation of the central-chest lymph nodes in 3D MDCT images

Central-chest lymph nodes play a vital role in lung-cancer staging. The definition of lymph nodes from three-dimensional (3D) multidetector computed-tomography (MDCT) images, however, remains an open problem. We propose two methods for computer-based segmentation of the central-chest lymph nodes from a 3D MDCT scan: the single-section live wire and the single-click live wire. For the single-section live wire, the user first applies the standard live wire to a single two-dimensional (2D) section after which automated analysis completes the segmentation process. The single-click live wire is similar but is almost completely automatic. Ground-truth studies involving human 3D MDCT scans demonstrate the robustness, efficiency, and intra-observer and inter-observer reproducibility of the methods.