A rapid micro-magnetic resonance imaging scanning for three-dimensional reconstruction of peripheral nerve fascicles

The most common methods for three-dimensional reconstruction of peripheral nerve fascicles include histological and radiology techniques. Histological techniques have many drawbacks including an enormous manual workload and poor image registration. Micro-magnetic resonance imaging（Micro-MRI）, an emerging radiology technique, has been used to report results in the brain, liver and tumor tissues. However, micro-MRI usage for obtaining intraneural structures has not been reported. The aim of this study was to present a new imaging method for three-dimensional reconstruction of peripheral nerve fascicles by ~1T micro-MRI. Freshly harvested sciatic nerve samples from an amputated limb were divided into four groups. Two different scanning conditions（Mannerist Solution/GD-DTPA contrast agent, distilled water） were selected, and both T1 and T2 phases programmed for each scanning condition. Three clinical surgeons evaluated the quality of the images via a standardized scale. Moreover, to analyze deformation of the two-dimensional image, the nerve diameter and total area of the micro-MRI images were compared after hematoxylin-eosin staining. The results show that rapid micro-MRI imaging method can be used for three-dimensional reconstruction of the fascicle structure. Nerve sample immersed in contrast agent（Mannerist Solution/GD-DTPA） and scanned in the T1 phase was the best. Moreover, the nerve sample was scanned freshly and can be recycled for other procedures. MRI images show better stability and smaller deformation compared with histological images. In conclusion, micro-MRI provides a feasible and rapid method for three-dimensional reconstruction of peripheral nerve fascicles, which can clearly show the internal structure of the peripheral nerve.

GPU-accelerated three-dimensional reconstruction method of the Compton camera and its application in radionuclide imaging

A novel and fast three-dimensional reconstruction method for a Compton camera and its performance in radionuclide imaging is proposed and analyzed in this study. The conical surface sampling back-projection method with scattering angle correction(CSS-BP-SC) can quickly perform the back-projection process of the Compton cone and can be used to precompute the list-mode maximum likelihood expectation maximization(LM-MLEM). A dedicated parallel architecture was designed for the graphics processing unit acceleration of the back-projection and iteration stage of the CSS-BP-SC-based LM-MLEM. The imaging results of the two-point source Monte Carlo(MC) simulation demonstrate that by analyzing the full width at half maximum along the three coordinate axes, the CSS-BP-SC-based LM-MLEM can obtain imaging results comparable to those of the traditional reconstruction algorithm, that is, the simple back-projection-based LM-MLEM. The imaging results of the mouse phantom MC simulation and experiment demonstrate that the reconstruction results obtained by the proposed method sufficiently coincide with the set radioactivity distribution, and the speed increased by more than 664 times compared to the traditional reconstruction algorithm in the mouse phantom experiment. The proposed method will further advance the imaging applications of Compton cameras.

Evaluating the use of three-dimensional reconstruction visualization technology for precise laparoscopic resection in gastroesophageal junction cancer

BACKGROUND Laparoscopic gastrectomy for esophagogastric junction(EGJ)carcinoma enables the removal of the carcinoma at the junction between the stomach and esophagus while preserving the gastric function,thereby providing patients with better treatment outcomes and quality of life.Nonetheless,this surgical technique also presents some challenges and limitations.Therefore,three-dimensional reconstruction visualization technology(3D RVT)has been introduced into the procedure,providing doctors with more comprehensive and intuitive anatomical information that helps with surgical planning,navigation,and outcome evaluation.AIM To discuss the application and advantages of 3D RVT in precise laparoscopic resection of EGJ carcinomas.METHODS Data were obtained from the electronic or paper-based medical records at The First Affiliated Hospital of Hebei North University from January 2020 to June 2022.A total of 120 patients diagnosed with EGJ carcinoma were included in the study.Of these,68 underwent laparoscopic resection after computed tomography(CT)-enhanced scanning and were categorized into the 2D group,whereas 52 underwent laparoscopic resection after CT-enhanced scanning and 3D RVT and were categorized into the 3D group.This study had two outcome measures:the deviation between tumor-related factors(such as maximum tumor diameter and infiltration length)in 3D RVT and clinical reality,and surgical outcome indicators(such as operative time,intraoperative blood loss,number of lymph node dissections,R0 resection rate,postoperative hospital stay,postoperative gas discharge time,drainage tube removal time,and related complications)between the 2D and 3D groups.RESULTS Among patients included in the 3D group,27 had a maximum tumor diameter of less than 3 cm,whereas 25 had a diameter of 3 cm or more.In actual surgical observations,24 had a diameter of less than 3 cm,whereas 28 had a diameter of 3 cm or more.The findings were consistent between the two methods(χ^(2)=0.346,P=0.556),with a kappa consistency coefficient of 0.808.With respect to infiltration length,in the 3D group,23 patients had a length of less than 5 cm,whereas 29 had a length of 5 cm or more.In actual surgical observations,20 cases had a length of less than 5 cm,whereas 32 had a length of 5 cm or more.The findings were consistent between the two methods(χ^(2)=0.357,P=0.550),with a kappa consistency coefficient of 0.486.Pearson correlation analysis showed that the maximum tumor diameter and infiltration length measured using 3D RVT were positively correlated with clinical observations during surgery(r=0.814 and 0.490,both P<0.05).The 3D group had a shorter operative time(157.02±8.38 vs 183.16±23.87),less intraoperative blood loss(83.65±14.22 vs 110.94±22.05),and higher number of lymph node dissections(28.98±2.82 vs 23.56±2.77)and R0 resection rate(80.77%vs 61.64%)than the 2D group.Furthermore,the 3D group had shorter hospital stay[8(8,9)vs 13(14,16)],time to gas passage[3(3,4)vs 4(5,5)],and drainage tube removal time[4(4,5)vs 6(6,7)]than the 2D group.The complication rate was lower in the 3D group(11.54%)than in the 2D group(26.47%)(χ^(2)=4.106,P<0.05).CONCLUSION Using 3D RVT,doctors can gain a more comprehensive and intuitive understanding of the anatomy and related lesions of EGJ carcinomas,thus enabling more accurate surgical planning.

Training image analysis for three-dimensional reconstruction of porous media

In order to obtain a better sandstone three-dimensional （3D） reconstruction result which is more similar to the original sample, an algorithm based on stationarity for a two-dimensional （2D） training image is proposed. The second-order statistics based on texture features are analyzed to evaluate the scale stationarity of the training image. The multiple-point statistics of the training image are applied to obtain the multiple-point statistics stationarity estimation by the multi-point density function. The results show that the reconstructed 3D structures are closer to reality when the training image has better scale stationarity and multiple-point statistics stationarity by the indications of local percolation probability and two-point probability. Moreover, training images with higher multiple-point statistics stationarity and lower scale stationarity are likely to obtain closer results to the real 3D structure, and vice versa. Thus, stationarity analysis of the training image has far-reaching significance in choosing a better 2D thin section image for the 3D reconstruction of porous media. Especially, high-order statistics perform better than low-order statistics.

Three-dimensional positions of scattering centers reconstruction from multiple SAR images based on radargrammetry

A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of targets are extracted from 2D SAR images. Secondly, similarity measure is developed based on 2D attributed scatter centers' location, type, and radargrammetry principle between multiple SAR images. By this similarity, we can associate 2D scatter centers and then obtain candidate 3D scattering centers. Thirdly, these candidate scattering centers are clustered in 3D space to reconstruct final 3D positions. Compared with presented methods, the proposed method has a capability of describing distributed scattering center, reduces false and missing 3D scattering centers, and has fewer restrictionson modeling data. Finally, results of experiments have demonstrated the effectiveness of the proposed method.

Three-Dimensional Model Reconstruction of Nonwovens from Multi-Focus Images

The three-dimensional(3D)model is of great significance to analyze the performance of nonwovens.However,the existing modelling methods could not reconstruct the 3D structure of nonwovens at low cost.A new method based on deep learning was proposed to reconstruct 3D models of nonwovens from multi-focus images.A convolutional neural network was trained to extract clear fibers from sequence images.Image processing algorithms were used to obtain the radius,the central axis,and depth information of fibers from the extraction results.Based on this information,3D models were built in 3D space.Furthermore,self-developed algorithms optimized the central axis and depth of fibers,which made fibers more realistic and continuous.The method with lower cost could reconstruct 3D models of nonwovens conveniently.

Three-dimensional Imaging of Multi-slice Spiral CT in Bronchial Artery Correlative Study on Blood Supply of Central Lung Cancer and Its Clinical Significance

Objective: To evaluate three-dimensional bronchial artery imaging charactersin central lung cancer and applied values with multi-slice spiral CT (MSCT) to provide theoreticalevidence on blood supply and intervention therapy. Methods: Eighteen patients with central lungcancer underwent MSCT with real time helical thin-slice CT scanning. Three-dimensional bronchialartery reconstruction was done at the console work-station. The space anatomical characters ofbronchial artery were observed through different rotations. Results: For 6 cases, thethree-dimensional images of bronchial artery (33.33%) could exactly show the origins, the routes(lung inner segment and mediatism segment) and the diameters of bronchial arteries. Vision rate ofbronchial arteries was the highest in pulmonary artery stricture and truncation groups, and thevessels' diameter became larger apparently. These characters demonstrated blood supply of this kindof central lung cancer come from bronchial artery. Volume rendering images were the best ones amongthree-dimensional images. Conclusion: Three-dimensional imaging with MSCT in bronchial artery canreveal the anatomical characters of bronchial artery and provide theoretical evidence on bloodsupply and intervention therapy of central lung cancer.

Research and Realization of Medical Image Fusion Based on Three-Dimensional Reconstruction

A new medical image fusion technique is presented.The method is based on three-dimensional reconstruction.After reconstruction,the three-dimensional volume data is normalized by three-dimensional coordinate conversion in the same way and intercepted through setting up cutting plane including anatomical structure,as a result two images in entire registration on space and geometry are obtained and the images are fused at last.Compared with traditional two-dimensional fusion technique,three-dimensional fusion technique can not only resolve the different problems existed in the two kinds of images,but also avoid the registration error of the two kinds of images when they have different scan and imaging parameter.The research proves this fusion technique is more exact and has no registration,so it is more adapt to arbitrary medical image fusion with different equipments.

Survey of methods and principles in three-dimensional reconstruction from two-dimensional medical images

Three-dimensional(3D)reconstruction of human organs has gained attention in recent years due to advances in the Internet and graphics processing units.In the coming years,most patient care will shift toward this new paradigm.However,development of fast and accurate 3D models from medical images or a set of medical scans remains a daunting task due to the number of pre-processing steps involved,most of which are dependent on human expertise.In this review,a survey of pre-processing steps was conducted,and reconstruction techniques for several organs in medical diagnosis were studied.Various methods and principles related to 3D reconstruction were highlighted.The usefulness of 3D reconstruction of organs in medical diagnosis was also highlighted.

Three-Dimensional Measurement and Reconstruction of Fabric Drape Shape

This paper introduces a new method of measuring the three-dimensional drape shape of fabrics with structural light. First, we apply parallel annular structural light to form light and shade alternating contour stripes on the surface of fabrics. We then collect the images of contour stripes using Charge Coupled Device (CCD). Subsequently, we process the images to identify the contour stripes and edges of fabrics, and obtain the fabric contour lines of curved surfaces. Finally, we apply three-dimensional curved surface modeling method based on a network of polar coordinates, and reconstruct the three-dimensional drape shape of fabrics. Experiments show that our method is effective in testing and reconstructing three-dimensional drape shape of fabrics.

Multidetector computed tomography three-dimensional and multiplanar reconstruction diagnosis of a rare cause of gastrointestinal bleeding: A case report

BACKGROUND Anastomosis of the testicular vein with the superior mesenteric vein rarely causes severe gastrointestinal bleeding.To date,there have been few studies describing its appearance on medical imaging.Here,we present multidetector computed tomography three-dimensional and multiplanar reconstruction(MPR)images of a typical digital subtraction angiography showing proven ectopic bleeding and provide the first review of the image performance.CASE SUMMARY A 68-year-old man who had been rushed to the hospital with a four-day history of melena and fainting underwent multiple esophagogastroduodenoscopy procedures that failed to identify the source of bleeding.We used MPR combined with three-dimensional reconstruction images,and found that the testicular vein had anastomosed with the superior mesenteric vein,and they clustered together in the jejunal vessel wall,which caused severe gastrointestinal bleeding.Digital subtraction angiography confirmed the location of bleeding.After transfusion and embolization therapy,the patient’s condition improved.CONCLUSION Computed tomography-MPR combined with three-dimensional images offers significant value in the localization and qualitative assessment of rare gastrointestinal hemorrhage.The features of multiphase spiral scanning can improve the accuracy of the diagnosis.

Digital measurement of bone tumor volume by CT three-dimensional reconstruction technology

Objective To discuss the measurement of bone tumor volume on the basis of three dimensional images segmentation technology. Methods Twenty patients with lacunar bone tumor from Tianjin Hospital and Tongji Hospital were included in the

Investigation of prior image constrained compressed sensing-based spectral X-ray CT image reconstruction

To improve spectral X-ray CT reconstructed image quality, the energy-weighted reconstructed image xbins^W and the separable paraboloidal surrogates（SPS） algorithm are proposed for the prior image constrained compressed sensing（PICCS）-based spectral X-ray CT image reconstruction. The PICCS-based image reconstruction takes advantage of the compressed sensing theory, a prior image and an optimization algorithm to improve the image quality of CT reconstructions.To evaluate the performance of the proposed method, three optimization algorithms and three prior images are employed and compared in terms of reconstruction accuracy and noise characteristics of the reconstructed images in each energy bin.The experimental simulation results show that the image xbins^W is the best as the prior image in general with respect to the three optimization algorithms; and the SPS algorithm offers the best performance for the simulated phantom with respect to the three prior images. Compared with filtered back-projection（FBP）, the PICCS via the SPS algorithm and xbins^W as the prior image can offer the noise reduction in the reconstructed images up to 80. 46%, 82. 51%, 88. 08% in each energy bin,respectively. M eanwhile, the root-mean-squared error in each energy bin is decreased by 15. 02%, 18. 15%, 34. 11% and the correlation coefficient is increased by 9. 98%, 11. 38%,15. 94%, respectively.

Construction and application of a three-dimensional vascular variation-based nephrometry scoring system for completely endophytic renal tumors

Background:Completely endophytic renal tumors(CERT)pose significant challenges due to their anatomical complexity and loss of visual clues about tumor location.A facile scoring model based on three-dimensional(3D)reconstructed images will assist in better assessing tumor location and vascular variations.Methods:In this retrospective study,80 patients diagnosed with CERT were included.Forty cases underwent preoperative assessment using 3D reconstructed imaging(3D-Cohort),while the remaining 40 cases were assessed using two-dimensional imaging(2D-Cohort).Vascular variations were evaluated by ascertaining the presence of renal arteries>1,prehilar branching arteries,and arteries anterior to veins.The proposed scoring system,termed RAL,encompassed three critical components:(R)adius(maximal tumor diameter in cm),(A)rtery(occurrence of arterial variations),and(L)ocation relative to the polar line.Comparison of the RAL scoring system was made with established nephrometry scoring systems.Results:A total of 48(60%)patients exhibited at least one vascular variation.In the 2D-Cohort,patients with vascular variations experienced significantly prolonged operation time,increased bleeding volume,and extended warm ischemia time compared with those without vascular variations.Conversely,the presence of vascular vari-ations did not significantly affect operative parameters in the 3D-Cohort.Furthermore,the 2D-Cohort demon-strated a notable decline in both short-and long-term estimated glomerular filtration rate(eGFR)changes com-pared with the 3D-Cohort,a trend consistent across patients with warm ischemia time≥25 min and those with vascular variations.Notably,the 2D-Cohort exhibited a larger margin of normal renal tissue compared with the 3D-Cohort.Elevated RAL scores correlated with larger tumor size,prolonged operation time,extended warm is-chemia time,and substantial postoperative eGFR decrease.The RAL scoring system displayed superior predictive capabilities in assessing postoperative eGFR changes compared with conventional nephrometry scoring systems.Conclusions:Our proposed 3D vascular variation-based nephrometry scoring system offers heightened proficiency in preoperative assessment,precise prediction of surgical complexity,and more accurate evaluation of postoper-ative renal function in CERT patients.

Image reconstruction based on total-variation minimization and alternating direction method in linear scan computed tomography

Linear scan computed tomography （LCT） is of great benefit to online industrial scanning and security inspection due to its characteristics of straight-line source trajectory and high scanning speed. However, in practical applications of LCT, there are challenges to image reconstruction due to limited-angle and insufficient data. In this paper, a new reconstruction algorithm based on total-variation （TV） minimization is developed to reconstruct images from limited-angle and insufficient data in LCT. The main idea of our approach is to reformulate a TV problem as a linear equality constrained problem where the objective function is separable, and then minimize its augmented Lagrangian function by using alternating direction method （ADM） to solve subproblems. The proposed method is robust and efficient in the task of reconstruction by showing the convergence of ADM. The numerical simulations and real data reconstructions show that the proposed reconstruction method brings reasonable performance and outperforms some previous ones when applied to an LCT imaging problem.

Reduction of artifacts in dental cone beam CT images to improve the three dimensional image reconstruction

Cone-beam CT (CBCT) scanners are based on volumetric tomography, using a 2D extended digital array providing an area detector [1,2]. Compared to traditional CT, CBCT has many advantages, such as less X-ray beam limitation, and rapid scan time, etc. However, in CBCT images the x-ray beam has lower mean kilovolt (peak) energy, so the metal artifact is more pronounced on. The position of the shadowed region in other views can be tracked by projecting the 3D coordinates of the object. Automatic image segmentation was used to replace the pixels inside the metal object with the boundary pixels. The modified projection data, using synthetically Radon Transformation, were then used to reconstruct a new back projected CBCT image. In this paper, we present a method, based on the morphological, area and pixel operators, which we applied on the Radon transformed image, to reduce the metal artifacts in CBCT, then we built the Radon back project images using the radon invers transformation. The artifacts effects on the 3d-reconstruction is that, the soft tissues appears as bones or teeth. For the preprocessing of the CBCT images, two methods are used to recognize the noisy black areas that the first depends on thresholding and closing algorithm, and the second depends on tracing boundaries after using thresholding algorithm too. The intensity of these areas is the lowest in the image than other tissues, so we profit this property to detect the edges of these areas. These two methods are applied on phantom and patient image data. It deals with reconstructed CBCT dicom images and can effectively reduce such metal artifacts. Due to the data of the constructed images are corrupted by these metal artifacts, qualitative and quantitative analysis of CBCT images is very essential.

Three-dimensional reconstructed magnetic resonance scans:Accuracy in identifying and defining knee meniscal tears

AIM To determine whether three-dimensional(3D) reconstruction from conventional magnetic resonance imaging(MRI) is able to accurately detect a meniscal tear, and define the configuration.METHODS Thirty-three patients' 3T MRI scan data were collected and sagittal uni-planar 3D reconstructions performed from the preoperative MRI. There were 24 meniscal tears in 24 patients, and nine controls. All patients had arthroscopic corroboration of MRI findings. Two independent observers prospectively reported on all 33 reconstructions. Meniscal tear presence or absence was noted, and tear configuration subsequently categorised as either radial, bucket-handle, parrot beak, horizontal or complex.RESULTS Identification of control menisci or meniscal tear presence was excellent(Accuracy: observer 1 = 90.9%; observer 2 = 81.8%). Of the tear configurations, bucket handle tears were accurately identified(Accuracy observer 1 and 2 = 80%). The remaining tear configurations were notaccurately discernable.CONCLUSION Uni-planar 3D reconstruction from 3T MRI knee scan sequences are useful in identifying normal menisci and menisci with bucket-handle tears. Advances in MRI sequencing and reconstruction software are awaited for accurate identification of the remaining meniscal tear configurations.

Three-Dimensional Reconstructed Finite Element Model for C/C Composites by Micro-CT

The precise microscopic feature of carbon-carbon（C/C） composites is essential {or an accurate predic tion of their mechanical behavior. After fabrication, actual microscopic feature differs from simple ideal spatial model. Micro computed lomography（CT） scan can well describe internal microstruetures of composites. Therefore, a reconstructed model is developed based on mireo-CT, by a series of prodcedures including extrac tlng components, generating new binary images and establishing a finite element （FE） model. Compared with the model designed by reconstructed commercial software MIMICS. the presented reconstructed FE model is superior in terms of high mesh quality and eontrollable mesh cluantity. The precision of the model is verified by experiment.

A practical image reconstruction and processing method for symmetrically off-center detector CBCT system

CBCT scanners have been widely used in angiography,radiotherapy guidance,mammography and oral maxillofacial imaging.To cut detector size,reduce manufacturing costs and radiation dose while keeping a reasonable FOV,the flat panel detector can be placed off-center horizontally.This scanning configuration extends the FOV effectively.However,each projection is transversely truncated,bringing errors and artifacts in reconstruction.In this paper,a simple but practical method is proposed for this scanning geometry based on truncation compensation and the modified FDK algorithm.Numerical simulations with jaw phantom were conducted to evaluate the accuracy and practicability of the proposed method.A novel CBCT system for maxillofacial imaging is used for clinical test,which is equipped with an off-center small size flat panel detector.Results show that reconstruction accuracy is acceptable for clinical use,and the image quality appears sufficient for specific diagnostic requirements.It provides a novel solution for clinical CBCT system,in order to reduce radiation dose and manufacturing cost.

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.