Breast MR segmentation and lesion detection with cellular neural networks and 3D template matching

A novel fully automated system is introduced to facilitate lesion detection in dynamic contrast-enhanced, magnetic resonance mammography (DCE-MRM). The system extracts breast regions from pre-contrast images using a cellular neural network, generates normalized maximum intensity-time ratio (nMITR) maps and performs 3D template matching with three layers of 12x12 cells to detect lesions. A breast is considered to be properly segmented when relative overlap >0.85 and misclassification rate <0.10. Sensitivity, false-positive rate per slice and per lesion are used to assess detection performance. The system was tested with a dataset of 2064 breast MR images (344slicesx6 acquisitions over time) from 19 women containing 39 marked lesions. Ninety-seven percent of the breasts were segmented properly and all the lesions were detected correctly (detection sensitivity=100%), however, there were some false-positive detections (31%/lesion, 10%/slice).     

Automatic lung nodule matching on sequential CT images

We propose an automatic segmentation and registration method that provides more efficient and robust matching of lung nodules in sequential chest computed tomography (CT) images. Our method consists of four steps. First, the lungs are extracted from chest CT images by the automatic segmentation method. Second, gross translational mismatch is corrected by optimal cube registration. This initial alignment does not require extracting any anatomical landmarks. Third, the initial alignment is step-by-step refined by hierarchical surface registration. To evaluate the distance measures between lung boundary points, a three-dimensional distance map is generated by narrow-band distance propagation, which drives fast and robust convergence to the optimal value. Finally, correspondences of manually detected nodules are established from the pairs with the smallest Euclidean distances. Experimental results show that our segmentation method accurately extracts lung boundaries and the registration method effectively finds the nodule correspondences.     

Lung metastases detection in CT images using 3D template matching

The aim of this study is to demonstrate a novel, fully automatic computer detection method applicable to metastatic tumors to the lung with a diameter of 4-20 mm in high-risk patients using typical computed tomography (CT) scans of the chest. Three-dimensional (3D) spherical tumor appearance models (templates) of various sizes were created to match representative CT imaging parameters and to incorporate partial volume effects. Taking into account the variability in the location of CT sampling planes cut through the spherical models, three offsetting template models were created for each appearance model size. Lung volumes were automatically extracted from computed tomography images and the correlation coefficients between the subregions around each voxel in the lung volume and the set of appearance models were calculated using a fast frequency domain algorithm. To determine optimal parameters for the templates, simulated tumors of varying sizes and eccentricities were generated and superposed onto a representative human chest image dataset. The method was applied to real image sets from 12 patients with known metastatic disease to the lung. A total of 752 slices and 47 identifiable tumors were studied. Spherical templates of three sizes (6, 8, and 10 mm in diameter) were used on the patient image sets; all 47 true tumors were detected with the inclusion of only 21 false positives. This study demonstrates that an automatic and straightforward 3D template-matching method, without any complex training or postprocessing, can be used to detect small lung metastases quickly and reliably in the clinical setting.     

基于3D ResUnet网络的肺结节分割

目的:将深度残差结构和U-Net网络结合形成新的网络ResUnet,并利用ResUnet深度学习网络结构对胸部CT影像进行图像分割以提取肺结节区域。方法:使用的CT影像数据来源于LUNA16数据集,首先对CT图像预处理提取出肺实质,然后对其截取立体图像块并进行数据增强来扩充样本数,形成相应的肺结节掩膜图像,最后将生成的样本输入到ResUnet模型中进行训练。结果:本研究模型最终的精度和召回率分别为35.02%和97.68%。结论:该模型能自动学习肺结节特征,为后续的肺癌自动诊断提供可靠基础,减少临床诊断的成本并节省医生诊断的时间。 【关键词】肺结节;分割;深度残差结构;召回率;ResUnet     

3D打印导航模板辅助置钉在儿童寰枢椎脱位治疗中的应用

目的探讨3D打印导航模板在儿童寰枢椎脱位治疗中的应用价值。方法选择2015年1月至2019年6月本院收治的16例儿童寰枢椎脱位患者作为研究对象,术前根据寰枢椎CT平扫及三维重建,将数据导入计算机软件后重建寰枢椎模型,设计理想置钉钉道,并结合寰枢椎后方表面骨性结构数据设计出个性化导板。术中使用导板辅助置入寰枢椎椎弓根螺钉。术后评价螺钉位置及治疗效果。结果共置入椎弓根螺钉64枚,寰椎和枢椎分别32枚。寰椎安全性评估系统结果为:0级螺钉28枚,1级螺钉2枚,2级螺钉2枚。枢椎安全性评估系统结果为:0级螺钉30枚,1级螺钉2枚。术中无脊髓、神经根及椎动脉损伤等并发症发生。16例均获得随访,随访时间5～24个月。15例患者在术后3个月后方植骨达到骨性融合; 1例齿状突骨折患者手术中后方未进行植骨,术后5个月复查可见齿状突愈合,于术后1年拆除内固定物。随访期间,所有患者螺钉位置良好,无断钉及松动等情况发生;末次随访,患者颈部疼痛症状缓解,10例存在脊髓受压表现者神经功能均恢复至ASIA分级E级。结论 3D打印导模板可提高儿童寰枢椎置钉的准确性和安全性,减少手术并发症,值得临床推荐。     

个体化3D打印导向模板在下颈椎椎弓根螺钉置钉中的应用研究

目的 通过数字化骨科技术制作出个体化导向模板,在导板引导下在下颈椎实物模型上置入椎弓根螺钉,并比较其与传统徒手置钉方法在置钉准确率方面的区别。方法 随机选取芜湖市第二人民医院2021年1月至2021年12月住院行颈椎CT三维重建的患者CT资料30例,通过Mimics软件进行三维重建,模拟椎弓根螺钉置钉,设计出最佳进针钉道。继而通过逆向工程软件提取设计出个体化反向模板,3D打印制作出椎体模型及带钉道的导向模板。在C₃-C₆椎体模型上采用随机数字法随机于一侧应用导向模板辅助置入椎弓根螺钉(导向模板组),另一侧徒手置钉(徒手置钉组),检查并比较两组的置钉准确率。结果 所有颈椎椎体模型双侧均顺利完成置钉,共240枚螺钉。导向模板组116枚螺钉(96.7%)位置为Ⅰ级,4枚螺钉(3.3%)为Ⅱ级,而徒手置钉组73枚螺钉位置为Ⅰ级(60.8%),17枚螺钉(14.1%)为Ⅱ级,11枚螺钉(9.2%)为Ⅲ级,19枚螺钉Ⅳ级(15.8%),两组比较差异有统计学意义(P<0.05)。结论 通过计算机辅助软件与3D打印机制作出个体化导向模板,在导板引导下在...     

颈椎弓根置钉植入的新型3D打印导板有效性研究

目的　通过评价新型3D打印的导板在手术中植入颈椎椎弓根螺钉的有效性,旨在为颈椎内固定器械操作提供准确和安全的方法。 方法　6例无病损成人颈椎标本,CT扫描后重建颈椎的三维数字化模型,根据颈椎椎板的具体的解剖形态特征,设计与颈椎椎板的特异性反向模板,3D 打印出颈椎的导航模块,保证进钉通道的方向和深度。采用个体化的3D导板技术, 6例标本植入84枚钉,X线片和CT图像评价术前设计的椎弓根钉进入的长度和宽度与术后实际符合程度。 结果　通过数字化技术打印的个体化3D导板与颈椎椎板吻合程度高度一致,可以控制植入螺钉方向和长度。采用此导板植入的84枚螺钉中,79枚螺钉位于椎体内,5例穿破椎弓根外出骨皮质,无椎板周围重要解剖结构损伤,椎弓根钉进入的长度符合率达到100%,椎弓根钉进入的宽度符合率达到94.05%。 结论 新型3D打印导板使颈椎椎弓根植入的长度和宽度均达到良好的可控性,并且提高了颈椎椎弓根植入的安全性和准确率。     

Advanced template matching method for estimation of intervertebral kinematics of lumbar spine

Diagnosis of low back pain and other degenerative spinal pathologies can be extremely difficult and, so far, there are not accepted standards. In general, such pathologies are associated with alteration of mechanical properties of spine and, in particular, with the instability of spinal motion. Intervertebral kinematics can be a valuable, objective method to assess the functionality of spinal segments. Fluoroscopic imaging system can provide continuous screening of lumbar tracts during patient's motion, with an acceptable low X-ray dose. Estimation of intervertebral kinematics relies on accurate recognition of vertebrae positions throughout the fluoroscopic sequence: specific vertebrae features are identified and tracked either by manual selection or by automated methods. This study presents a new method of vertebra tracking, based on image template matching of the contour of the vertebral body for an accurate intervertebral kinematics analysis. An image gradient operator was utilized to obtain the vertebral contours; it operates after an edge-preserving smoothing filter designed to reduce low dose X-ray image noise. Once a template is defined for each vertebra, this is used to determine the best vertebral location in each image throughout the fluoroscopic sequence. Accuracy of the proposed method was tested using images of a calibration model. Average error achieved for the intervertebral angle is of the order of 0.4° and approximately 2 mm for the intervertebral centre of rotation. Five fluoroscopic lumbar sequences of healthy volunteers undergoing passive flexion–extension motion were processed. The intervertebral kinematics was compared with other methods (automated and manual) by an estimation of measurement error. Results showed that the current method provides a better representation of the evolution over time of kinematic parameters. In particular, root mean square differences between the current method and a manual selection procedure performed by an experienced and trained clinician resulted 1.3° for the intervertebral angles and 0.9 mm for the intervertebral trajectory. The proposed method provides an effective, automated and objective technique for estimation of intervertebral kinematics of lumbar spine.     

基于CT影像分析的肺结节计算机辅助检测与诊断技术进展

肺结节是肺部最常见的病变之一,肺结节的早期检测和诊断对于肺癌的早期诊治十分重要.近年来,随着多层螺旋CT(MSCT)、高分辨CT(HRCT)及低剂量胸部CT(LDCT)的应用,计算机辅助诊断(CAD)系统的必要性和重要性也日益显现.由于CAD系统可以明显提高诊断医生的工作效率,为更多的患者服务,因此成为国内外相关领域专家的研究热点,近几年来也取得了一定的成果.就肺结节的CT计算机辅助检测和诊断的基本方法和应用作一综述. Abstract： Lung nodules are one of the most common pathological changes, thus early detection of lung nodule is very important for the diagnosis medical treatment of lung eancer. In recent years, as the application of multi-slice spiral CT(MSCT), high-resolution CT(HRCT) and low-dose chest CTCLDCT), computer-aided diagnosis (CAD) system will be more essential and more important. Since CAD system can improve the working efficiency of doctors and provide service to more patients, has become the research hotspot and achievement has been made in relevant area internationally recently. This review summarizes the basic methods and applieations of computer-aided detection and diagnosis of lung nodule based on CT image.     

Pleural nodule identification in low-dose and thin-slice lung computed tomography

A completely automated system for the identification of pleural nodules in low-dose and thin-slice computed tomography (CT) of the lung has been developed. The directional-gradient concentration method has been applied to the pleura surface and combined with a morphological opening-based procedure to generate a list of nodule candidates. Each nodule candidate is characterized by 12 morphological and textural features, which are analyzed by a rule-based filter and a neural classifier. This detection system has been developed and validated on a dataset of 42 annotated CT scans. The k-fold cross validation has been used to evaluate the neural classifier performance. The system performance variability due to different ground truth agreement levels is discussed. In particular, the poor 44% sensitivity obtained on the ground truth with agreement level 1 (nodules annotated by only one radiologist) with six FP per scan grows up to the 72% if the underlying ground truth is changed to the agreement level 2 (nodules annotated by two radiologists).     

3D打印导航模板辅助特发性脊柱侧弯椎弓根螺钉置入的准确性

背景:特发性脊柱侧弯手术置钉操作难度大,手术时间长,采用3D打印导航模板辅助置钉可降低手术难度,优化置钉操作,提升置钉效果,具有显著优势。目的:探讨3D打印导航模板辅助置钉在特发性脊柱侧弯椎弓根螺钉内固定矫形术中的应用价值。方法:回顾性分析2018年1月至2019年8月采用椎弓根螺钉内固定矫形治疗的17例特发性脊柱侧弯患者的临床资料,8例术中应用3D打印导航模板辅助置钉(3D组),9例术中常规徒手置钉(常规组)?术后采用CT扫描螺钉位置评估置钉等级与可接受率;比较2组置钉时间、术中X射线透视次数、置钉出血量、置钉等级、置钉可接受率、二次置钉率、主弯矫形率和置钉相关并发症。结果与结论:①17例患者均顺利完成置钉操作,术中无置钉相关的血管、神经损伤并发症出现。常规组术后出现1例背部疼痛,1例下肢疼痛,经对症治疗后症状消失。②3D组置钉时间短于常规组,术中X射线透视次数、置钉出血量小于常规组,差异均有显著性意义(P<0.05)。③3D组置钉等级、置钉可接受率优于常规组,二次置钉率小于常规组,差异均有显著性意义(P<0.05)。④2组主弯矫形率比较,差异无显著性意义(P>0.05)。⑤提示特发性脊柱侧弯椎弓根螺钉置入内固定矫形过程中采用3D打印导航模板辅助置钉可降低置钉难度,提升置钉准确率。     

Lung nodule detection in low-dose and thin-slice computed tomography

A computer-aided detection (CAD) system for the identification of small pulmonary nodules in low-dose and thin-slice CT scans has been developed. The automated procedure for selecting the nodule candidates is mainly based on a filter enhancing spherical-shaped objects. A neural approach based on the classification of each single voxel of a nodule candidate has been purposely developed and implemented to reduce the amount of false-positive findings per scan. The CAD system has been trained to be sensitive to small internal and sub-pleural pulmonary nodules collected in a database of low-dose and thin-slice CT scans. The system performance has been evaluated on a data set of 39 CT containing 75 internal and 27 sub-pleural nodules. The FROC curve obtained on this data set shows high values of sensitivity to lung nodules (80-85% range) at an acceptable level of false positive findings per patient (10-13 FP/scan).     

Fast segmentation of bone in CT images using 3D adaptive thresholding

Fast bone segmentation is often important in computer-aided medical systems. Thresholding-based techniques have been widely used to identify the object of interest (bone) against dark backgrounds. However, the darker areas that are often present in bone tissue may adversely affect the results obtained using existing thresholding-based segmentation methods. We propose an automatic, fast, robust and accurate method for the segmentation of bone using 3D adaptive thresholding. An initial segmentation is first performed to partition the image into bone and non-bone classes, followed by an iterative process of 3D correlation to update voxel classification. This iterative process significantly improves the thresholding performance. A post-processing step of 3D region growing is used to extract the required bone region. The proposed algorithm can achieve sub-voxel accuracy very rapidly. In our experiments, the segmentation of a CT image set required on average less than 10 s per slice. This execution time can be further reduced by optimizing the iterative convergence process.     

新型3D打印导板辅助颈椎前路双侧椎弓根置钉的安全及可行性

文题释义：3D 打印手术导板：该导板依据手术需要,通过计算机辅助设计、3D打印制备出的一种具有术中准确定位点、置钉的位置、方向和深度,精确建立孔道、截面、空间距离、相互成角关系及其他复杂空间结构等功能的辅助手术器械,具有获取途径方便、使用方法简单、价格低廉等优点。 颈椎前路椎弓根置钉：是一种区别于传统颈椎后路椎弓根螺钉置钉技术的新型置钉技术,该技术可通过单独前方入路实现颈椎三柱损伤或多节段病变的坚强固定,无需再行后路固定,可有效减少手术创伤和并发症。 背景：下颈椎前路椎弓根螺钉固定技术可通过前方入路实现颈椎坚强固定,具有较大的应用前景。但该技术操作难度大、风险高,目前尚未得到广泛应用。 目的：改良设计一种用于下颈椎双侧前路椎弓根螺钉置钉的3D打印导板,探讨其辅助颈椎前路椎弓根螺钉置钉的可行性及安全性。 方法：选取6具正常成人颈椎标本,男女各3具,行薄层CT扫描后将影像数据以DICOM格式导入Mimics 17.0软件,三维重建后模拟设计出C₃-C₇双侧颈椎前路椎弓根螺钉钉道导孔,再以颈椎椎体前面、椎体上面前1/2及双侧钩突关节面前1/2骨性结构为标志,反向增厚设计生成导孔基座,形成颈椎前路椎弓根螺钉置钉导板。经3D打印得到导板实体后,在导板辅助下行C₃-C₇双侧颈椎前路椎弓根螺钉置钉。将置钉后的颈椎标本再次行CT扫描,通过CT断面影像评价置钉准确性。同时利用Mimics17.0软件比较实际钉道与模拟钉道在横断面的内、外偏移角度(α1、α2)差异及其在矢状面的上、下偏移角度(β1、β2)差异。 结果与结论：①双侧共计60枚颈椎前路椎弓根螺钉均顺利置入,其中57枚完全位于椎弓根皮质内,判定为0级,准确率95.0%;另外3枚破出椎弓根皮质,其中1级2枚(3.3%),2级1枚(1.7%);②真实钉道与模拟钉道相比,其横断面内、外偏移角分别为(0.867±0.787)°、(0.783±0.792)°,差异无显著性意义(P > 0.05);矢状面上、下偏移角分别为(1.362±1.380)°、(1.314±1.300)°,差异无显著性意义(P > 0.05)。③提示在设计得到的3D打印导板辅助下可顺利完成下颈椎双侧前路椎弓根螺钉置钉,且具有良好的置钉安全性。 ORCID: 0000-0003-0124-7585(肖强)中国组织工程研究杂志出版内容重点：人工关节;骨植入物;脊柱;骨折;内固定;数字化骨科;组织工程     

一种断层图像间复杂轮廓的三维重建方法

提出了一种新的断层图像间复杂轮廓的三维重建方法。该方法基于空间距离、几何相似性和重建三维表面平滑性的准则,较好地解决了一对一和一对多分叉轮廓的匹配问题。在单轮廓匹配过程中,结合几何距离最近和双向最近邻相似准则,避免了其它算法中对阈值敏感的问题,提高了匹配的准确性和自动化程度。在一对多的分叉轮廓匹配中,区分不同的情况以进行不同的处理,得到了较满意的三维重建结果。     

基于3DV-Net的肺结节检测分割算法

目的：提出基于深度学习的肺结节识别与分割算法,以辅助医生进行肺部疾病检测。方法：针对LUNA16数据集数据量大以及肺结节种类大小多样性等特征,采用基于改进的深度神经网络3DV-Net实现多种肺结节的检测分割,然后使用ResNet对结节图像和非结节图像进行分类。对LUNA16数据集中的肺部CT图像进行图像去噪、插值采样等预处理,然后生成粗分割图像和Mask图像,再使用改进的3DV-Net模型对数据进行多次训练预测。网络层级越深,出现梯度消散、梯度爆炸等问题的概率越大,改进的3DV-Net使用残差连接来改善这一问题。结果：改进的3DV-Net的Dice相似系数和IoU分别达到88.29%和88.25%。结论：本文方法有助于肺结节的检测分割,在肺结节的辅助诊断方面有重要意义。     

螺旋CT三维重建在腰椎滑脱症诊断及手术中的价值

目的探讨螺旋CT三维重建在腰椎滑脱症诊断及手术中的价值。方法对比47例腰椎滑脱症病人的X线片、CT及螺旋CT三维重建图像，结合术中椎弓根钉定位及对于是否为峡部裂的不同处理，分析螺旋CT三维重建在腰椎滑脱症的诊断价值。结果47例均为腰椎前滑脱，三种检查方法对椎弓峡部的成像存在不同，螺旋CT三维重建可清楚显示椎弓峡部的全貌和裂隙，指导手术定位。结论螺旋CT三维重建能较好地评价椎弓峡部裂所致的病理解剖改变，指导临床制订完善的手术方案，具有很大的优越性及应用前景。     

3D printing of MRI compatible components: Why every MRI research group should have a low-budget 3D printer

PurposeTo evaluate low budget 3D printing technology to create MRI compatible components.Material and methodsA 3D printer is used to create customized MRI compatible components, a loop-coil platform and a multipart mouse fixation. The mouse fixation is custom fit for a dedicated coil and facilitates head fixation with bite bar, anesthetic gas supply and biomonitoring sensors. The mouse fixation was tested in a clinical 3T scanner.ResultsAll parts were successfully printed and proved MR compatible. Both design and printing were accomplished within a few days and the final print results were functional with well defined details and accurate dimensions (Δ <  0.4 mm). MR images of the mouse head clearly showed reduced motion artifacts, ghosting and signal loss when using the fixation.ConclusionsWe have demonstrated that a low budget 3D printer can be used to quickly progress from a concept to a functional device at very low production cost. While 3D printing technology does impose some restrictions on model geometry, additive printing technology can create objects with complex internal structures that can otherwise not be created by using lathe technology. Thus, we consider a 3D printer a valuable asset for MRI research groups.     

3D vs. 2D cephalometric analysis comparisons with repeated measurements from 20 Thai males and 20 Thai females

This paper presented 3D cephalometric analysis on DICOM data from I-CAT CT cone-beam machine consisted of averages and standard deviations from 20 Thai males from 19 to 70 year (average 33.53 ± 14.08 year) and 20 Thai females from 16 to 70 year (average 32.60 ± 15.37 year). The angular measurements consisted of 49 lateral angular measurements and 9 frontal angular measurements while linear measurements consisted of 29 lateral linear measurements, 3 frontal linear measurements, and 8 perpendicular measurements. Results in 3D were compared with the corresponding 2D results showing that most midline-to-midline linear measurements and some midline-to-midline angular measurements were not different, while other types of measurements were significantly different. The 3D results will be used in the clinical Ceph3D services as requested by those with interests on cephalometric analysis and anthropology with focus on Thai subjects while the 2D results will be used for comparison with cephalometric analyses from other orthodontists.ts reserved.     

椎弓根螺钉导航模板在上颈椎手术中的应用

目的探讨上颈椎手术中椎弓根螺钉导航模板(Pedicle screw navigational template,PSNT)辅助椎弓根螺钉(Pedicle screw,PS)植入的准确性和可行性。方法回顾性分析我科室收治的12例上颈椎畸形患者。术前根据患者上颈椎CT平扫数据获得个体化PSNT,并在手术过程中使用PSNT辅助PS的植入。术后观察患者CT平扫图像中PS与椎弓根和骨皮质的位置关系,并判断螺钉位置的优劣等级。结果 12例患者共放置34枚PS 34枚,其中20枚置入C_2、8枚置入C_3、2枚置入C_4、2枚置入C_5。PS位置Ⅰ级31枚(91.2%)、Ⅱ级2枚(5.9%)、Ⅲ级1枚(2.9%)、Ⅳ级0枚。优良率为97.1%。结论在上颈椎手术中,PSNT为一有效可靠的导航方法,且能够显著降低术中电离辐射的暴露时间。值得在上颈椎手术中开展应用。