直线加速器机载锥形束CT图像散射的修正方法

目的 对直线加速器机载锥形束CT(CBCT)散射修正方法进行研究.方法 在CBCT射线源前放置一个"指交叉"形的阻挡光栅,对Catphan 504模体进行扫描,分别获得CBCT图像和扇形束CT图像.利用基于阈值的图像分割算法跟踪机架旋转过程中阻挡光栅在CBCT图像中的位置,提取散射样本后利用插值法估计散射信号分布,采用改进的半扇扫描重建算法重建散射修正后的图像.结果 散射修正后的Catphan 504模体图像与扇形束CT重建的图像接近.与散射修正前比较,散射修正后CT值误差从100.86 HU下降到15.74 HU,散射修正后低对比度分辨力平均提高1.37倍.结论 基于阈值的图像分割算法准确跟踪阻挡光栅的位置,在铅片区域可采集散射信号,其余区域可通过改进的半扇扫描算法完成单次扫描的图像重建.     

Cephalogram synthesis and landmark detection in dental cone-beam CT systems

Due to the lack of a standardized 3D cephalometric analysis methodology, 2D cephalograms synthesized from 3D cone-beam computed tomography (CBCT) volumes are widely used for cephalometric analysis in dental CBCT systems. However, compared with conventional X-ray film based cephalograms, such synthetic cephalograms lack image contrast and resolution, which impairs cephalometric landmark identification. In addition, the increased radiation dose applied to acquire the scan for 3D reconstruction causes potential health risks. In this work, we propose a sigmoid-based intensity transform that uses the nonlinear optical property of X-ray films to increase image contrast of synthetic cephalograms from 3D volumes. To improve image resolution, super resolution deep learning techniques are investigated. For low dose purpose, the pixel-to-pixel generative adversarial network (pix2pixGAN) is proposed for 2D cephalogram synthesis directly from two cone-beam projections. For landmark detection in the synthetic cephalograms, an efficient automatic landmark detection method using the combination of LeNet-5 and ResNet50 is proposed. Our experiments demonstrate the efficacy of pix2pixGAN in 2D cephalogram synthesis, achieving an average peak signal-to-noise ratio (PSNR) value of 33.8 with reference to the cephalograms synthesized from 3D CBCT volumes. Pix2pixGAN also achieves the best performance in super resolution, achieving an average PSNR value of 32.5 without the introduction of checkerboard or jagging artifacts. Our proposed automatic landmark detection method achieves 86.7% successful detection rate in the 2 mm clinical acceptable range on the ISBI Test1 data, which is comparable to the state-of-the-art methods. The method trained on conventional cephalograms can be directly applied to landmark detection in the synthetic cephalograms, achieving 93.0% and 80.7% successful detection rate in 4 mm precision range for synthetic cephalograms from 3D volumes and 2D projections, respectively.     

Upper airway segmentation and dimensions estimation from cone-beam CT image datasets

Objective To segment and measure the upper airway using cone-beam computed tomography (CBCT). This information may be useful as an imaging biomarker in the diagnostic assessment of patients with obstructive sleep apnea and in the planning of any necessary therapy. Methods With Institutional Review Board Approval, anonymous CBCT datasets from subjects who had been imaged for a variety of conditions unrelated to the airway were evaluated. DICOM images were available. A segmentation algorithm was developed to separate the bounded upper airway and measurements were performed manually to determine the smallest cross-sectional area and the anteriorposterior distance of the retropalatal space (RP-SCA and RP-AP, respectively) and retroglossal space (RG-SCA and RG-AP, respectively). A segmentation algorithm was developed to separate the bounded upper airway and it was applied to determine RP-AP, RG-AP, the smallest transaxial-sectional area (TSCA) and largest sagittal view airway area (LCSA). A second algorithm was created to evaluate the airway volume within this bounded upper airway. Results Measurements of the airway segmented automatically by the developed algorithm agreed with those obtained using manual segmentation. The corresponding volumes showed only very small differences considered clinically insignificant. Conclusion Automatic segmentation of the airway imaged using CBCT is feasible and this method can be used to evaluate airway cross-section and volume comparable to measurements extracted using manual segmentation.     

Automated implant segmentation in cone-beam CT using edge detection and particle counting

Purpose

To develop a fully automated, accurate and robust segmentation technique for dental implants on cone-beam CT (CBCT) images.

Methods

A head-size cylindrical polymethyl methacrylate phantom was used, containing titanium rods of 5.15 mm diameter. The phantom was scanned on 17 CBCT devices, using a total of 39 exposure protocols. Images were manually thresholded to verify the applicability of adaptive thresholding and to determine a minimum threshold value \(({T}_{\mathrm{min}})\) . A three-step automatic segmentation technique was developed. Firstly, images were pre-thresholded using \({T}_{\mathrm{min}}\) . Next, edge enhancement was performed by filtering the image with a Sobel operator. The filtered image was thresholded using an iteratively determined fixed threshold \(({T}_{\mathrm{edge}})\) and converted to binary. Finally, a particle counting method was used to delineate the rods. The segmented area of the titanium rods was compared to the actual area, which was corrected for phantom tilting.

Results

Manual thresholding resulted in large variation in threshold values between CBCTs. After applying the edge-enhancing filter, a stable \({T}_{\mathrm{edge}}\) value of 7.5 % was found. Particle counting successfully detected the rods for all but one device. Deviations between the segmented and real area ranged between \(-\) 2.7 and + \(14.4\,\hbox {mm}^{2}\) with an average absolute error of \(2.8\,\hbox {mm}^{2}\) . Considering the diameter of the segmented area, submillimeter accuracy was seen for all but two data sets.

Conclusion

A segmentation technique was defined which can be applied to CBCT data for an accurate and fully automatic delineation of titanium rods. The technique was validated in vitro and will be further tested and refined on patient data.     

16-bit CT图像读取金属植入物CT值的应用

目的 探讨16-bit CT图像在读取金属植入物CT值中的应用价值。方法 于模体中间分别插入一圆柱形铝棒、钛合金棒和不锈钢棒,对模体进行CT扫描,对图像重建获得12-bit和16-bit CT图像。分析并比较3种金属棒的12-bit和16-bit图像及其CT值。结果 对于同种金属棒,12-bit图像和16-bit图像显示效果基本相同。铝棒周围未显示出伪影;钛合金棒周围有较明显的放射状伪影;不锈钢棒周围有严重伪影。3种金属棒内部的显示无明显差异。12-bit和16-bit图像中,铝棒的最大CT值分别为2 159 HU和2 150 HU,平均CT值分别为2 026 HU、2 021 HU;钛合金棒的最大CT值分别为3 071 HU和6 950 HU,平均CT值分别为3 071 HU、5 957 HU;不锈钢棒的最大CT值分别为3 071 HU和12 060 HU,平均CT值分别为3 071 HU、9 397 HU。结论 16-bit的CT图像能够显示体内金属植入物的CT值分布,分辨出铝、钛合金或不锈钢的金属植入物。     

Deep learning solution for medical image localization and orientation detection

Magnetic Resonance (MR) imaging plays an important role in medical diagnosis and biomedical research. Due to the high in-slice resolution and low through-slice resolution nature of MR imaging, the usefulness of the reconstruction highly depends on the positioning of the slice group. Traditional clinical workflow relies on time-consuming manual adjustment that cannot be easily reproduced. Automation of this task can therefore bring important benefits in terms of accuracy, speed and reproducibility. Current auto-slice-positioning methods rely on automatically detected landmarks to derive the positioning, and previous studies suggest that a large, redundant set of landmarks are required to achieve robust results. However, a costly data curation procedure is needed to generate training labels for those landmarks, and the results can still be highly sensitive to landmark detection errors. More importantly, a set of anatomical landmark locations are not naturally produced during the standard clinical workflow, which makes online learning impossible. To address these limitations, we propose a novel framework for auto-slice-positioning that focuses on localizing the canonical planes within a 3D volume. The proposed framework consists of two major steps. A multi-resolution region proposal network is first used to extract a volume-of-interest, after which a V-net-like segmentation network is applied to segment the orientation planes. Importantly, our algorithm also includes a Performance Measurement Index as an indication of the algorithm’s confidence. We evaluate the proposed framework on both knee and shoulder MR scans. Our method outperforms state-of-the-art automatic positioning algorithms in terms of accuracy and robustness.     

Intra-operative adjustment of standard planes in C-arm CT image data

Purpose

With the help of an intra-operative mobile C-arm CT, medical interventions can be verified and corrected, avoiding the need for a post-operative CT and a second intervention. An exact adjustment of standard plane positions is necessary for the best possible assessment of the anatomical regions of interest but the mobility of the C-arm causes the need for a time-consuming manual adjustment. In this article, we present an automatic plane adjustment at the example of calcaneal fractures.

Methods

We developed two feature detection methods (2D and pseudo-3D) based on SURF key points and also transferred the SURF approach to 3D. Combined with an atlas-based registration, our algorithm adjusts the standard planes of the calcaneal C-arm images automatically. The robustness of the algorithms is evaluated using a clinical data set. Additionally, we tested the algorithm’s performance for two registration approaches, two resolutions of C-arm images and two methods for metal artifact reduction.

Results

For the feature extraction, the novel 3D-SURF approach performs best. As expected, a higher resolution (\(512^3\) voxel) leads also to more robust feature points and is therefore slightly better than the \(256^3\) voxel images (standard setting of device). Our comparison of two different artifact reduction methods and the complete removal of metal in the images shows that our approach is highly robust against artifacts and the number and position of metal implants.

Conclusions

By introducing our fast algorithmic processing pipeline, we developed the first steps for a fully automatic assistance system for the assessment of C-arm CT images.

     

锥形束CT图像引导对肺癌放疗摆位误差分析及CTV-PTV外放边界的研究

目的:该研究旨在通过千伏锥形束CT(cone-beam CT,CBCT)对肺癌调强放疗摆位误差分析,确定临床靶区(clinical target volume,CTV)外扩至计划靶区(planning target volume,PTV)边界的大小.方法:2019年1—12月在我院全程进行图像引导放射治疗的63例肺癌患...     

Fast lung nodule detection in chest CT images using cylindrical nodule-enhancement filter

Purpose

Existing computer-aided detection schemes for lung nodule detection require a large number of calculations and tens of minutes per case; there is a large gap between image acquisition time and nodule detection time. In this study, we propose a fast detection scheme of lung nodule in chest CT images using cylindrical nodule-enhancement filter with the aim of improving the workflow for diagnosis in CT examinations.

Methods

Proposed detection scheme involves segmentation of the lung region, preprocessing, nodule enhancement, further segmentation, and false-positive (FP) reduction. As a nodule enhancement, our method employs a cylindrical shape filter to reduce the number of calculations. False positives (FPs) in nodule candidates are reduced using support vector machine and seven types of characteristic parameters.

Results

The detection performance and speed were evaluated experimentally using Lung Image Database Consortium publicly available image database. A 5-fold cross-validation result demonstrates that our method correctly detects 80 % of nodules with 4.2 FPs per case, and detection speed of proposed method is also 4–36 times faster than existing methods.

Conclusion

Detection performance and speed indicate that our method may be useful for fast detection of lung nodules in CT images.     

锥形束CT在放射治疗中的应用

影像引导下的放射治疗是近年来出现的一种治疗恶性肿瘤的新技术,而锥形束CT既是一种全新的CT成像技术,又是影像引导下放射治疗系统的关键设备。本文介绍锥形束CT的基本原理及其在放射治疗中的应用现状和研究进展情况,并对锥形束CT图像后处理技术进行综述。     

Intraoperative visualization of cerebral oxygenation using hyperspectral image data: a two-dimensional mapping method

Purpose

Superficial temporal artery (STA)—middle cerebral artery (MCA) bypass is an important technique for cerebrovascular reconstruction. Intraoperative hemodynamic imaging is needed to perform cerebrovascular reconstruction safely and effectively. Optical intrinsic signal (OIS) imaging is commonly used for assessing cerebral hemodynamics in experimental studies, because it can provide high-resolution mapping images. However, OIS is not used clinically due to algorithm, instrumentation and spectral resolution limitations. We tested the feasibility of a hyperspectral camera (HSC) for assessment of cortical hemodynamics with spectral imaging of the cerebral cortex in rats and in vivo humans.

Methods

A hyperspectral camera (HSC) was tested in a rat model of cerebral ischemia (middle cerebral artery occlusion) and during human revascularization surgery (STA–MCA anastomosis). Changes in cortical oxygen saturation were derived from spectral imaging data (400–800 nm) collected by exposing the cortex to Xenon light. Reflected light was sampled using the HSC. The system was then tested intraoperatively during superficial temporal artery to middle cerebral artery anastomosis procedures. Comparison with single-photon emission computed tomography (SPECT) imaging data was done.

Results

During middle cerebral artery occlusion in rats, the HSC technique showed a significant decrease in cortical oxygen saturation in the ischemic hemisphere. In clinical cases, the cortical oxygen saturation was increased after STA–MCA anastomosis, which agreed with the SPECT imaging data.

Conclusion

Continuous collection of imaging spectroscopic data is feasible and may provide reliable quantification of the hemodynamic responses in the brain. The HSC system may be useful for monitoring intraoperative changes in cortical surface hemodynamics during revascularization procedures in humans.     

Intra-operative assessment of fractured articular surfaces in cone beam CT image data

Purpose

The assessment of intra-operatively acquired volumetric data is a difficult and often time-consuming task, which demands a new set of skills from the surgeons. In the case of orthopedic surgeries such as the treatment of calcaneal fractures, the correctness of the reduction of the bone fragments can be verified with the help of C-arm CT volumetric images. For an accurate intra-operative assessment of the displaced fragments, an automatic segmentation of the articular surfaces and color-coded visualization was developed.

Methods

Our automatic approach consists of three major steps: first, using adjusted standard planes intersecting the articular region, the joint space is localized with an intensity profile-based method. In a second step, the localized joint space is segmented on the Laplacian of Gaussian filtered volumetric image by a modified binary flood fill algorithm. Finally, a 3D surface model of the segmented joint space is analyzed and visualized with focus on critical displacements of the surface.

Results

A specifically designed human cadaver study consisting of ten lower legs of ten different donors was conducted to acquire 48 realistic C-arm CT images of misaligned bone fragments (steps of varying sizes) in the posterior talar articular surface of the calcaneus. The proposed algorithmic pipeline was verified by the acquired image data and showed very good results with no false positives and an overall correct displacement assessment of \(93.8\,\%\).

Conclusions

The proposed algorithmic pipeline can be easily integrated into the clinical workflow and qualifies for intra-operative usage. It showed very good results on the reference data set of the cadaver study. With the help of such an assistance system, the time-consuming process of 2D view adjustment and visual assessment of the gray value images can be greatly simplified.

     

非等中心锥束CT成像系统标定及三维重建

目的 研究非等中心锥束CT系统(CBCT)几何参数标定及投影图像重排, 提出新的方法以提高参数标定精度及三维(3D)重建质量, 以期突破现有算法要求等中心系统应用环境的限制。方法 针对非等中心CBCT系统建立坐标系, 推导标定模型中特定标志点空间坐标与其在投影图像中平面坐标之间的几何关系, 建立虚拟等中心CBCT系统, 提出面向非等中心CBCT系统的解析+迭代混合标定方法, 对投影图像进行重排, 在此基础上进行3D重建。将标定模型置于非等中心CBCT系统中, 获取各个旋转角度下的投影图像;提取投影图像中特定标志点坐标, 基于这些坐标数据, 采用所提方法计算虚拟等中心CBCT系统几何参数;并求取虚拟等中心锥束投影图像;最后采用FDK算法进行3D重建。结果 与文献[10]算法相比, 所提算法对转轴在成像板上的投影坐标(u^0' 和v^0' )标定精度相当, 而射线源到成像板的垂直距离(D')和射线源到转轴的距离(R')标定精度明显较优。结论 本研究混合标定算法可提高D'和R'的标定精度, 并可突破文献[10]算法等中心系统应用环境的限制。     

Intraoperative ultrasonic localization of a small pancreatic pseudocyst

Intraoperative pancreatic ultrasound can be useful to identify small masses or cysts that are not readily palpable at surgery. In our case, a small (2.0 cm diameter) pseudocyst was demonstrated preoperatively by ultrasound and computed tomography, but could not be palpated at surgery. Intraoperative ultrasound located and helped to guide needle aspiration of the pancreatic pseudocyst. Other indications for intraoperative pancreatic ultrasound are reviewed.     

Varian 23 EX 加速器附加锥形束CT图像均匀性分析

目的 分析Varian 23 EX 加速器附加KV X线锥形束CT(CBCT)在不同扫描条件下图像均匀性的变化。方法 采用安装在直线性加速器上的CBCT系统,在标准头/体部扫描条件下重复扫描体模,并将数据通过放疗网络传至计划系统及Matlab 7.0,利用Eclips计划系统评价获取图像在x、y及z轴方向上的均匀性变化,并与传统扇形束CT(FBCT)扫描重建图像的测量结果进行比较。结果 CBCT图像在标准头/体部扫描条件下,在三个轴向上均有良好的对称性和均匀性。在标准头部扫描方式下CT值的波动范围分别为:x轴±25 HU,y轴±30 HU,z轴±20 HU。在标准体部扫描模式下,CT值的波动范围略大。等中心横断面x,y轴方向上具有最佳的对称性和均匀性。相对于x,y轴方向,z轴具有更佳的对称性和均匀性。Bowtie滤过器能够明显减少模体散射线,可提高图像的均匀性。结论 Varian 23 EX 加速器附加KV X线CBCT图像均匀度好,通过对CT值校正,CBCT可以用于治疗计划系统的剂量计算。     

大视野对比常规视野锥形束CT在经动脉化疗栓塞术中的应用

目的比较数字减影血管造影(digital substraction angiography, DSA)大视野(field-of-view, FOV)锥形束计算机断层扫描(cone-beam computed tomography, CBCT)与常规FOV CBCT在经动脉化疗栓塞术(transarterial chemoembolization, TACE)中的应用价值。方法 选择2021年10月至12月接受TACE治疗的肝癌患者37例,随机分为大视野组(n=20)和对照组(n=17)。大视野组在术中行大FOV CBCT扫描;对照组行常规CBCT扫描。对两组患者的影像学资料、透视和曝光时间及辐射剂量进行分析,比较两组图像质量和辐射剂量。结果 大视野组3D图像质量达优率为90%,高于对照组的58.82%(P=0.028)。大视野组与对照组平均曝光次数、平均累计透视时间、平均累计曝光时间和空气比释动能差异均无统计学意义。大视野组单位时间剂量面积乘积(dose area product,DAP)低于对照组[(26.852±6.430)μGymm²/s vs (53.12...     

CT scan range estimation using multiple body parts detection: let PACS learn the CT image content

Purpose

The aim of this study was to develop an efficient CT scan range estimation method that is based on the analysis of image data itself instead of metadata analysis. This makes it possible to quantitatively compare the scan range of two studies.

Methods

In our study, 3D stacks are first projected to 2D coronal images via a ray casting-like process. Trained 2D body part classifiers are then used to recognize different body parts in the projected image. The detected candidate regions go into a structure grouping process to eliminate false-positive detections. Finally, the scale and position of the patient relative to the projected figure are estimated based on the detected body parts via a structural voting. The start and end lines of the CT scan are projected to a standard human figure. The position readout is normalized so that the bottom of the feet represents 0.0, and the top of the head is 1.0.

Results

Classifiers for 18 body parts were trained using 184 CT scans. The final application was tested on 136 randomly selected heterogeneous CT scans. Ground truth was generated by asking two human observers to mark the start and end positions of each scan on the standard human figure. When compared with the human observers, the mean absolute error of the proposed method is 1.2 % (max: 3.5 %) and 1.6 % (max: 5.4 %) for the start and end positions, respectively.

Conclusion

We proposed a scan range estimation method using multiple body parts detection and relative structure position analysis. In our preliminary tests, the proposed method delivered promising results.

     

基于条状挡板的kV级锥形束CT散射校正

目的 校正锥形束CT投影中的散射信号,以提高图像质量。 方法 使用条状挡板测量Varian机载kV级锥形束CT投影图像中的散射信号,并将其从再次扫描的投影中扣除,以获得原始射线的投影图像。使用空域自适应的BayesShrink小波对投影图像进行去噪处理,并导入Varian On Board Imager工作站进行重建;比较处理前后的图像质量。 结果 校正后图像的低对比度分辨力提高,噪声降低,CT值的准确性和均匀性得到改善。 结论 条状挡板能准确获取投影图像中的散射信号;扣除散射信号后使用小波阈值法去噪,可有效提高图像质量。     

经济型PET/CT与双源CT异机融合在肿瘤诊断中的应用

目的通过对比分析经济型PET/CT与双源CT异机融合的图像质量,探讨异机融合的临床应用价值。方法对29例可疑肿瘤或肿瘤复发转移患者行经济型PET/CT的PET与双源CT图像融合,并与同机融合图像质量进行对比分析。结果两种方法均检出原发灶和转移灶共46个,异机融合图像质量优于同机融合(χ2=14.743,P<0.001)。结论双源CT与经济型PET/CT异机融合,方便实用,优势互补,可提高图像质量,对临床诊断和治疗肿瘤有重要价值。