Comparison of the Imaging Manifestations and Diagnostic Values of Multi-slice Spiral CT and Enhanced MRI Scans of Primary Liver Cancer(PLC)Intrahepatic Lesions

Objective:To compare and analyze the clinical diagnostic value of multi-slice spiral CT and enhanced MRI for primary liver cancer(PLC),and to summarize the imaging findings.Methods:The research subjects in this article were 50 patients with PLC who were admitted to our hospital from 2017 April to 2018 September.After the patients were admitted,they were examined by multi-slice spiral CT and enhanced MRI scanning,and the pathological diagnosis results were followed up.Relevant information was reviewed and analyzed.Results:The detection rate of multi-slice spiral CT was higher than that of MRI in the portal venous phase lesion detection.The difference was statistically significant(P<0.05).The detection rate of lesions in the arterial phase and delayed phase was not statistically significant(P>0.05);the diagnostic accuracy of multi-slice spiral CT was 85.96%,and the diagnostic accuracy of enhanced MRI scanning was 91.11%,which was not statistically significant(P>0.05).MRI scans showed the capsules of primary liver cancer better than CT,but the difference was not statistically significant(P>0.05).Conclusion:In conclusion,both multi-slice spiral CT and enhanced MRI can be used for the effective diagnosis of primary liver cancer intrahepatic lesions.The diagnostic value of the two is equivalent,but enhanced MRI has a slightly higher diagnostic accuracy and can be used as the preferred method.

The diagnostic value of 3D spiral CT imaging of cholangiopancreatic ducts on obstructive jaundice

Objective: Computerized tomography (CT) plays an important role in the diagnosis of diseases of biliary tract. Recently, three dimensions (3D) spiral CT imaging has been used in surgical diseases gradually. This study was designed to evaluate the diagnostic value of 3D spiral CT imaging of cholangiopancreatic ducts on obstructive jaundice. Methods: Thirty patients with obstructive jaundice had received B-mode ultrasonography, CT, percutaneous transhepatic cholangiography (PTC) or endoscopic retrograde cholangiopancreatography (ERCP), and 3D spiral CT imaging of cholangiopancreatic ducts preoperatively. Then the diagnose accordance rate of these examinational methods were compared after operations. Results: The diagnose accordance rate of 3D spiral CT imaging of cholangiopancreatic ducts was higher than those of B-mode ultrasonography, CT, or single PTC or ERCP, which showed clear images of bile duct tree and pathological changes. As to malignant obstructive jaundice, this examinational technique could clearly display the adjacent relationship between tumor and liver tissue, biliary ducts, blood vessels, and intrahepatic metastases. Conclusion: 3D spiral CT imaging of cholangiopancreatic ducts has significant value for obstructive diseases of biliary ducts, which provides effective evidence for the feasibility of tumor-resection and surgical options.

Multi-slice Spiral CT Three-dimensional Portography in Portal Vein Tumor Thrombus of Hepatic Cancer

Objective: To study the clinical significance of multi-slice spiral CT 3-dimensional (3D) portography in portal vein tumor thrombosis of hepatocellular cacinoma.Methods: 57 cases undergoing 3D portography were collected, of which 6 cases were normal, 5 cases were subjected to cirrhosis and hypertension of portal vein, 42 cases had portal tumor thrombus of hepatic cancer, and the remaining 4 cases showed lymph node enlargment in hilar of liver. All data of the patients came from conventional multi-slice spiral CT double phase of liver. Contrast media was 1.5–2 ml/kg with the injection rate being 2.5–3 ml/s. Axis and 3D portography was analyzed and compared in 42 cases of portal tumor thrombus of hepatic cancer.Results: According to portal tumor thrombus position, 42 cases were fallen into three categories: left (13 cases), right (20 cases), main (9 cases) of potal vein. There was no difference between axis and 3D portography in displaying portal tumor thrombus of hepatic cancer (P>0.05), but 3D portography showing collateral branches was better than axis portography after main portal vein thrombus.Conclusion: Multi-slice spiral CT 3D portography can display the position and types of portal tumor thrombus of hepatic cancer. 3D combined with axis portography can better evaluate the portal tumor thrombus of hepatic cancer and guide to select the therapies. Key words portal vein - tumor thrombus - multi-slice CT - 3 dimension imaging

Predicting 3D Radiotherapy Dose-Volume Based on Deep Learning

Cancer is one of the most dangerous diseaseswith highmortality.One of the principal treatments is radiotherapy by using radiation beams to destroy cancer cells and this workflow requires a lot of experience and skill from doctors and technicians.In our study,we focused on the 3D dose prediction problem in radiotherapy by applying the deeplearning approach to computed tomography(CT)images of cancer patients.Medical image data has more complex characteristics than normal image data,and this research aims to explore the effectiveness of data preprocessing and augmentation in the context of the 3D dose prediction problem.We proposed four strategies to clarify our hypothesis in different aspects of applying data preprocessing and augmentation.In strategies,we trained our custom convolutional neural network model which has a structure inspired by the U-net,and residual blocks were also applied to the architecture.The output of the network is added with a rectified linear unit(Re-Lu)function for each pixel to ensure there are no negative values,which are absurd with radiation doses.Our experiments were conducted on the dataset of the Open Knowledge-Based Planning Challenge which was collected from head and neck cancer patients treatedwith radiation therapy.The results of four strategies showthat our hypothesis is rational by evaluating metrics in terms of the Dose-score and the Dose-volume histogram score(DVH-score).In the best training cases,the Dose-score is 3.08 and the DVH-score is 1.78.In addition,we also conducted a comparison with the results of another study in the same context of using the loss function.

Use of various CT imaging methods for diagnosis of acute ischemic cerebrovascular disease

Thirty-four patients with cerebral infarction and 18 patients with transient ischemic attack were examined by multi-slice spiral CT scan, CT perfusion imaging, and CT angiography within 6 hours after onset. By CT perfusion imaging, 29 cases in the cerebral infarction group and 10 cases in the transient ischemic attack group presented with abnormal blood flow perfusion, which corresponded to the clinical symptoms. By CT angiography, various degrees of vascular stenosis could be detected in 41 patients, including 33 in the cerebral infarction group and eight in the transient ischemic attack group. The incidence of intracranial artery stenosis was higher than that of extracranial artery stenosis. The intracranial artery stenosis was located predominantly in the middle cerebral artery and carotid artery siphon, while the extracranial artery stenosis occurred mainly in the bifurcation of the common carotid artery and the opening of the vertebral artery. There were 34 cases （83%） with convict vascular stenosis and perfusion abnormalities, and five cases （45%） with perfusion abnormalities but without convict vascular stenosis. The incidence of cerebral infarction in patients with National Institutes of Health Stroke Scale scores 〉 5 points during onset was significantly higher than that in patients with National Institutes of Health Stroke Scale scores 〈 5 points. These experimental findings indicate that the combined application of various CT imaging methods allows early diagnosis of acute ischemic cerebrovascular disease, which can comprehensively analyze the pathogenesis and severity of acute ischemic cerebrovascular disease at the morphological and functional levels.

Study on threshold segmentation of multi-resolution 3D human brain CT image

In order to effectively improve the pathological diagnosis capability and feature resolution of 3D human brain CT images,a threshold segmentation method of multi-resolution 3D human brain CT image based on edge pixel grayscale feature decomposition is proposed in this paper.In this method,first,original 3D human brain image information is collected,and CT image filtering is performed to the collected information through the gradient value decomposition method,and edge contour features of the 3D human brain CT image are extracted.Then,the threshold segmentation method is adopted to segment the regional pixel feature block of the 3D human brain CT image to segment the image into block vectors with high-resolution feature points,and the 3D human brain CT image is reconstructed with the salient feature point as center.Simulation results show that the method proposed in this paper can provide accuracy up to 100%when the signal-to-noise ratio is 0,and with the increase of signal-to-noise ratio,the accuracy provided by this method is stable at 100%.Comparison results show that the threshold segmentation method of multi-resolution 3D human brain CT image based on edge pixel grayscale feature decomposition is signicantly better than traditional methods in pathological feature estimation accuracy,and it effectively improves the rapid pathological diagnosis and positioning recognition abilities to CT images.

口腔MSCT-3D与COPT对比研究

目的:通过与COPT对比,探究口腔MSCT-3D在临床中应用价值。材料和方法:COPT及MSCT各117例,COPT经计算机后处理,MSCT经工作站三维重建,根据影像结果,按金属牙、缺如和半残等项分别统计分析COPT及MSCT检查情况,并对摄影方法及影像后处理、摄影条件及照射剂量等项进行比较。结果:COPT牙齿正常9人(0.24%),正常记数3160颗(84.4%),异常记数551颗(15.6%),MSCT-3D牙齿正常11人(0.29%),正常记数3138颗(83.8%),异常记数606颗(16.2%)。摄影方式,COPT属曲面摄影,MSCT属断面螺旋摄影;影像后处理,COPT侧重2D曲面,2D效果优于MSCT,MSCT侧重3D立体,可行多种三维重建,3D效果优于COPT。照射剂量,MSCT远高于COPT。结论:口腔COPT2D影像性征显著;MSCT-3D在2D基础上,3D效果增加,但口腔专用,辐射剂量相对过大。

Using receiver operating characteristic curves to evaluate the diagnostic value of the combination of multislice spiral CT and alpha-fetoprotein levels for small hepatocellular carcinoma in cirrhotic patients

BACKGROUND： The various combination of multiphase enhancement multislice spiral CT （MSCT） makes the diagno- sis of a small hepatocellular carcinoma （sHCC） on the back- ground of liver cirrhosis possible. This study was to explore whether the combination of MSCT enhancement scan and alpha-fetoprotein （AFP） level ficiency for sHCC. could increase the diagnostic ef- METHODS： This study included 35 sHCC patients and 52 cir- rhotic patients without image evidence of HCC as a control group. The diagnoses were made by three radiologists em- ploying a 5-point rating scale, with postoperative pathologic results as the gold standard. Receiver operating characteristic （ROC） curve analysis was performed to evaluate the diag- nostic value of the three MSCT combination modes （arterial phase＋portal-venous phase, arterial phase＋delayed phase, arterial phase＋portal-venous phase＋delayed phase） and AFP levels for sHCC on the background of liver cirrhosis. RESULTS： The area under ROC curve （AUC）, sensitivity, and specificity of the combination of arterial phase＋portal- venous phase＋delayed phase were 0.93, 93%, and 82%, respectively. The average AUC of the arterial phase＋portal- venous phase＋delayed phase combination was significantly greater than that of the arterial phase＋portal-venous phase （AUC=0.84, P=0.01） and arterial phase＋delayed phase （AUC=0.85, P=0.03）. Arterial phase＋portal-venous phase had a smaller AUC （0.84） than arterial phase＋delayed phase （0.85）, but the difference was insignificant （P=0.15）. After combining MSCT enhancement scan with AFP, the AUC, sensitivity, and specificity were 0.95, 94%, and 83%, respectively, indicating a greatly increased diagnostic efficiency for sHCC. CONCLUSIONS： The combination of AFP and 3 phases MSCT enhancement scan could increase the diagnostic efficiency for sHCC on the background of liver cirrhosis. The application of ROC curve analysis has provided a new method and reference in HCC diagnosis.

Computer‑aided CT image processing and modeling method for tibia microstructure

We present a method for computed tomography(CT)image processing and modeling for tibia microstructure,achieved by using computer graphics and fractal theory.Given the large-scale image data of tibia species with DICOM standard for clinical applications,we take advantage of algorithms such as image binarization,hot pixel removing and close operation to obtain visually clear image for tibia microstructure.All of these images are based on 20 CT scanning images with 30μm slice thickness and 30μm interval and continuous changes in pores.For each pore,we determine its profile by using an improved algorithm for edge detection.Then,to calculate its three-dimensional fractal dimension,we measure the circumference perimeter and area of the pores of bone microstructure using a line fitting method based on the least squares.Subsequently,we put forward an algorithm for the pore profiles through ellipse fitting.The results show that the pores have significant fractal characteristics because of the good linear correlation between the perimeter and the area parameters in log–log scale coordinates system,and the ratio of the elliptical short axis to the long axis through ellipse fitting tends to 0.6501.Based on support vector machine and structural risk minimization principle,we put forward a mapping database theory of structure parameters among the pores of CT images and fractal dimension,Poisson’s ratios,porosity and equivalent aperture.On this basis,we put forward a new concept for 3D modeling called precision-measuring digital expressing to reconstruct tibia microstructure for human hard tissue.

PC-BASED SURFACE RECONSTRUCTION OF MEDICAL CT IMAGES

It is an active research area to reconstruct 3-D object and display its visible surfacesfrom cross-sectional images. In this paper, the methods of reconstructing 3-D object from medicalCT images and displaying the visible surfaces are discussed. A polygon approximation methodthat forms polygon with the same number of segment points and a fast interpolation method forcross-sectional contours are presented at first. Then the voxel set of a human liver is reconstructed.And then the liver voxel set is displayed using depth and gradient shading methods. The softwareis written in C programming language at a microcomputer image processing system with a PC/ATcomputer as the host and a PC-VISION board as the image processing unit. The result of theprocessing is satisfying.

Research on Automatic Elimination of Laptop Computer in Security CT Images Based on Projection Algorithm and YOLOv7-Seg

In civil aviation security screening, laptops, with their intricate structural composition, provide the potential for criminals to conceal dangerous items. Presently, the security process necessitates passengers to individually present their laptops for inspection. The paper introduced a method for laptop removal. By combining projection algorithms with the YOLOv7-Seg model, a laptop’s three views were generated through projection, and instance segmentation of these views was achieved using YOLOv7-Seg. The resulting 2D masks from instance segmentation at different angles were employed to reconstruct a 3D mask through angle restoration. Ultimately, the intersection of this 3D mask with the original 3D data enabled the successful extraction of the laptop’s 3D information. Experimental results demonstrated that the fusion of projection and instance segmentation facilitated the automatic removal of laptops from CT data. Moreover, higher instance segmentation model accuracy leads to more precise removal outcomes. By implementing the laptop removal functionality, the civil aviation security screening process becomes more efficient and convenient. Passengers will no longer be required to individually handle their laptops, effectively enhancing the efficiency and accuracy of security screening.

Designing a High-Performance Deep Learning Theoretical Model for Biomedical Image Segmentation by Using Key Elements of the Latest U-Net-Based Architectures

Deep learning (DL) has experienced an exponential development in recent years, with major impact in many medical fields, especially in the field of medical image and, respectively, as a specific task, in the segmentation of the medical image. We aim to create a computer assisted diagnostic method, optimized by the use of deep learning (DL) and validated by a randomized controlled clinical trial, is a highly automated tool for diagnosing and staging precancerous and cervical cancer and thyroid cancers. We aim to design a high-performance deep learning model, combined from convolutional neural network (U-Net)-based architectures, for segmentation of the medical image that is independent of the type of organs/tissues, dimensions or type of image (2D/3D) and to validate the DL model in a randomized, controlled clinical trial. We used as a methodology primarily the analysis of U-Net-based architectures to identify the key elements that we considered important in the design and optimization of the combined DL model, from the U-Net-based architectures, imagined by us. Secondly, we will validate the performance of the DL model through a randomized controlled clinical trial. The DL model designed by us will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. The combined model we designed takes into account the key features of each of the architectures Overcomplete Convolutional Network Kite-Net (Kite-Net), Attention gate mechanism is an improvement added on convolutional network architecture for fast and precise segmentation of images (Attention U-Net), Harmony Densely Connected Network-Medical image Segmentation (HarDNet-MSEG). In this regard, we will create a comprehensive computer assisted diagnostic methodology validated by a randomized controlled clinical trial. The model will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. This would help drastically minimize the time and effort that specialists put into analyzing medical images, help to achieve a better therapeutic plan, and can provide a “second opinion” of computer assisted diagnosis.

Visualization of Three-dimensional Human Data Based on CT Image

Three-dimensional medical image visualization becomes an essential part for medical field, including computer aided diagnosis, surgery planning and simulation, artificial limb surgery, radiotherapy planning, and teaching etc. In this paper, marching cubes algorithm is adopted to reconstruct the 3-D images for the CT image sequence in DICOM format under theVC＋＋6.0 and the visual package VTK platform. The relatively simple interactive operations such as rotation and transfer can be realized on the platform. Moreover, the normal vector and interior point are calculated to form the virtual clipping plane, which is then used to incise the 3-D object. Information of the virtual slice can be obtained, in the mean while the virtual slice images are displayed on the screen. The technique can realize the real time interaction extraction of virtual slice on 3-D CT image. The cuboids structured can be zoomed, moved and eircumrotated by operating mouse to incise the 3-D reconstruction object. Real time interaction can be realized by clipping the reconstruction object. The coordinates can be acquired by the mouse clicking in the 3D space, to realize the point mouse pick-up as well angle and distance interactive measurement. We can get quantitative information about 3-D images through measurement.

混凝土CT图像的3维重建技术

为了建立更加真实的3维混凝土细观模型,进行破损机理的分析。利用3维图像处理软件MIMICS对原始的CT图像进行预处理,实现了混凝土真实细观结构的3维重建,将重建结果导入到大型商业有限元软件ANSYS中,建立了更加能准确表征混凝土细观非均质性的3维有限元数值模型。在此基础上,对重建的细观有限元模型进行了数值模拟,并与其它有限元模型的分析结果进行了比较。结果表明:所建立的3维混凝土细观模型可以弥补传统随机混凝土骨料模型的不足,较好地反映出混凝土材料内部的力学特性,为最终能够深入研究混凝土材料的细观破损机理开辟新的途径。

Analysis of CT and MRI in the Diagnosis of Shoulder Joint Injury

Objective: To observe the effect of multi-slice spiral CT and magnetic resonance imaging (MRI) in the diagnosis of shoulder injury. Methods: 120 patients with shoulder injury who were treated in our hospital (January 2020 to December 2021) and underwent surgical treatment were diagnosed as shoulder injury. They were divided into CT group, MRI group and joint diagnosis group. The detection rates of the two methods were compared. Results: In the diagnosis of shoulder injury, MRI group was higher than CT group, and the joint diagnosis group was higher than the other two groups. Conclusion: In the diagnosis of shoulder injury, the joint examination of multi-slice spiral CT and magnetic resonance imaging (MRI) can obtain a higher diagnostic rate and ideal effect.

A Systematic Literature Review of Deep Learning Algorithms for Segmentation of the COVID-19 Infection

Coronavirus has infected more than 753 million people,ranging in severity from one person to another,where more than six million infected people died worldwide.Computer-aided diagnostic(CAD)with artificial intelligence(AI)showed outstanding performance in effectively diagnosing this virus in real-time.Computed tomography is a complementary diagnostic tool to clarify the damage of COVID-19 in the lungs even before symptoms appear in patients.This paper conducts a systematic literature review of deep learning methods for classifying the segmentation of COVID-19 infection in the lungs.We used the methodology of systematic reviews and meta-analyses(PRISMA)flow method.This research aims to systematically analyze the supervised deep learning methods,open resource datasets,data augmentation methods,and loss functions used for various segment shapes of COVID-19 infection from computerized tomography(CT)chest images.We have selected 56 primary studies relevant to the topic of the paper.We have compared different aspects of the algorithms used to segment infected areas in the CT images.Limitations to deep learning in the segmentation of infected areas still need to be developed to predict smaller regions of infection at the beginning of their appearance.

利用X射线CT技术研究根系三维构型的进展

【目的】X射线CT扫描具有非破坏性、高分辨率等特点,近年来被广泛应用于研究植物根系三维构型。本文介绍了X射线CT技术研究植物根系的原理和方法,并重点阐述了CT图像提取和定量根系的方法。【主要进展】X射线CT可以穿透土体进而获取土体三维结构,并能通过图像分析准确定量土体内部的细节特征(如根系、孔隙等)。目前根系结构研究中应用的CT主要有医用CT、工业显微CT、同步辐射CT等,分别用于研究不同大小和分辨率要求的样品。应用CT扫描根系样品时,样品的制备和扫描参数的选择非常重要,样品的尺寸、容器的材质、扫描功率和扫描时长等因素都会影响CT图像质量。CT图像中提取根系的方法包括全局阈值法、区域生长法、根系追踪法、深度学习法等,结合图像预处理和后处理能更完整地提取根系。利用ImageJ、Rootrak、RooTh等软件,可以定量根系形态学参数(体积、根长、直径等),还可以分析根系三维分布特征(根系生长角度、根系生长深度等)。【展望】从CT图像中提取根系的算法在实际应用中仍存在很多问题,开发提取根系的先进算法,准确获取根系三维构型并将其定量表征,仍将是CT技术用于根系研究的重要方向。由于CT设备性能的特点,扫描样品尺寸和图像分辨率的矛盾仍然是关键问题,X射线CT硬件设备的创新和发展对其在根系研究中更加广泛和有效的应用具有重要意义。

螺旋CT三维成像在颈椎损伤病变中的应用

目的 探讨螺旋CT三维成像 (MPR、SSD)在颈椎损伤中的应用价值。材料与方法 经X线和 /或螺旋CT证实的颈椎损伤 15例 ,行螺旋CT扫描 ,并作MPR和SSD成像 ,13例扫描参数为层厚 3mm ,床速 4.5mm/s ,重建间距 1.5mm ;2例为层厚 5mm ,床速5mm/s ,重建间距 2mm。SSD最低阈值选择 15 0～ 180。结果 椎体及附件骨折 10例 ,其中 6例伴环齿关节脱位 ,1例椎体滑脱。椎体旋转脱位 4例 ,成角滑脱 1例。 15例中 3例椎管狭窄并硬脊膜受压。MPR结合轴位图像可完全明确骨折、脱位及椎管情况。SSD对颈椎表面骨折、椎体旋转及成角脱位显示良好 ,立体感强 ,但对椎体内骨裂或骨折、椎管内病变显示差。结论 颈椎损伤应首选CT检查。轴位图像、MPR及SSD联合应用 ,能明确病变性质 ,立体、直观、多方位提供临床医师所需信息 ,有利于治疗方案的选择。

螺旋CT三维重建在腕关节损伤诊断中的应用

目的:探讨螺旋CT三维重建成像方法及其在腕关节损伤诊断中的价值。方法:对36例腕关节进行CT容积扫描,层厚1～3mm,层距1～3mm。将所有原始图像进行低对比及高对比薄层重建,然后将重建图像分别导入CT3D工作站,利用后处理软件MPR、MIP及SSD分别对腕关节进行成像,由两位CT诊断医生一起对各种后处理图像进行观察和分析。结果:全组病例的薄层重建及三维重建显示腕舟骨骨折35例,合并舟骨月骨周围脱位8例;三角骨骨折3例;大多角骨骨折1例。螺旋CT三维重建图像能全面、直观地显示相应的腕关节骨折、脱位及关节腔内骨片情况,尤其是MPR对骨折、脱位、骨碎片显示率为100%。结论:螺旋CT薄层MPR是一种无创伤性显示腕关节形态的最佳方法,其相关CT表现可为临床诊断腕关节损伤、制定手术方案提供可靠依据。

螺旋CT三维肾盂造影对肾实质占位性病变的诊断价值

目的 初步研究螺旋CT肾盂造影对肾实质占位性病变的诊断价值。材料与方法 肾癌 18例 ,肾囊肿 14例 ,肾血管平滑肌脂肪瘤 3例共 3 5例作前瞻性增强研究 ,注射对比剂 80～ 10 0ml后延迟 4分 3 0秒行肾脏输尿管上段螺旋CT扫描 ,回顾性重建间隔2 .5mm ,重建图像传送至工作站。采用多轴向多方位重建 (multiplanarprojectionvolumeticreconstruction ,MPVR)及最大密度投影法(MIP)重建。结果 肾盂显示佳 ,观察病灶与肾盂关系更为明确 ,病灶形态显示更为全面。结论 螺旋CT肾盂造影有助于肾实质占位病变的诊断和鉴别诊断 ,在 1次检查中可达到多种目的。