Sparse-view neutron CT 3D image reconstruction algorithm based on split Bregman method

As a complement to X-ray computed tomography(CT),neutron tomography has been extensively used in nuclear engineer-ing,materials science,cultural heritage,and industrial applications.Reconstruction of the attenuation matrix for neutron tomography with a traditional analytical algorithm requires hundreds of projection views in the range of 0°to 180°and typically takes several hours to complete.Such a low time-resolved resolution degrades the quality of neutron imaging.Decreasing the number of projection acquisitions is an important approach to improve the time resolution of images;however,this requires efficient reconstruction algorithms.Therefore,sparse-view reconstruction algorithms in neutron tomography need to be investigated.In this study,we investigated the three-dimensional reconstruction algorithm for sparse-view neu-tron CT scans.To enhance the reconstructed image quality of neutron CT,we propose an algorithm that uses OS-SART to reconstruct images and a split Bregman to solve for the total variation(SBTV).A comparative analysis of the performances of each reconstruction algorithm was performed using simulated and actual experimental data.According to the analyzed results,OS-SART-SBTV is superior to the other algorithms in terms of denoising,suppressing artifacts,and preserving detailed structural information of images.

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.

Drishti Paint 3.2:a new open-source tool for both 2D and 3D segmentation

X-ray computed tomography(CT)has been an important technology in paleontology for several decades.It helps researchers to acquire detailed anatomical structures of fossils non-destructively.Despite its widespread application,developing an efficient and user-friendly method for segmenting CT data continues to be a formidable challenge in the field.Most CT data segmentation software operates on 2D interfaces,which limits flexibility for real-time adjustments in 3D segmentation.Here,we introduce Curves Mode in Drishti Paint 3.2,an open-source tool for CT data segmentation.Drishti Paint 3.2 allows users to manually or semi-automatically segment the CT data in both 2D and 3D environments,providing a novel solution for revisualizing CT data in paleontological studies.

Image processing based three-dimensional model reconstruction for cross-platform numerical simulation

Numerical simulation is the most powerful computational and analysis tool for a large variety of engineering and physical problems.For a complex problem relating to multi-field,multi-process and multi-scale,different computing tools have to be developed so as to solve particular fields at different scales and for different processes.Therefore,the integration of different types of software is inevitable.However,it is difficult to perform the transfer of the meshes and simulated results among software packages because of the lack of shared data formats or encrypted data formats.An image processing based method for three-dimensional model reconstruction for numerical simulation was proposed,which presents a solution to the integration problem by a series of slice or projection images obtained by the post-processing modules of the numerical simulation software.By means of mapping image pixels to meshes of either finite difference or finite element models,the geometry contour can be extracted to export the stereolithography model.The values of results,represented by color,can be deduced and assigned to the meshes.All the models with data can be directly or indirectly integrated into other software as a continued or new numerical simulation.The three-dimensional reconstruction method has been validated in numerical simulation of castings and case studies were provided in this study.

A novel technique of three-dimensional reconstruction segmentation and analysis for sliced images of biological tissues

A novel technique of three-dimensional (3D) reconstruction, segmentation, display and analysis of series slices of images including microscopic wide field optical sectioning by deconvolution method, cryo-electron microscope slices by Fou-rier-Bessel synthesis and electron tomography (ET), and a series of computed tomography (CT) was developed to perform si-multaneous measurement on the structure and function of biomedical samples. The paper presents the 3D reconstruction seg-mentation display and analysis results of pollen spore, chaperonin, virus, head, cervical bone, tibia and carpus. At the same time, it also puts forward some potential applications of the new technique in the biomedical realm.

3D Shape Reconstruction of Lumbar Vertebra From Two X-ray Images and a CT Model

Structure reconstruction of 3 D anatomy from biplanar X-ray images is a challenging topic. Traditionally, the elastic-model-based method was used to reconstruct 3 D shapes by deforming the control points on the elastic mesh. However, the reconstructed shape is not smooth because the limited control points are only distributed on the edge of the elastic mesh.Alternatively, statistical-model-based methods, which include shape-model-based and intensity-model-based methods, are introduced due to their smooth reconstruction. However, both suffer from limitations. With the shape-model-based method, only the boundary profile is considered, leading to the loss of valid intensity information. For the intensity-based-method, the computation speed is slow because it needs to calculate the intensity distribution in each iteration. To address these issues, we propose a new reconstruction method using X-ray images and a specimen’s CT data. Specifically, the CT data provides both the shape mesh and the intensity model of the vertebra. Intensity model is used to generate the deformation field from X-ray images, while the shape model is used to generate the patient specific model by applying the calculated deformation field.Experiments on the public synthetic dataset and clinical dataset show that the average reconstruction errors are 1.1 mm and1.2 mm, separately. The average reconstruction time is 3 minutes.

Deep-Learning-Empowered 3D Reconstruction for Dehazed Images in IoT-Enhanced Smart Cities

With increasingly more smart cameras deployed in infrastructure and commercial buildings,3D reconstruction can quickly obtain cities’information and improve the efficiency of government services.Images collected in outdoor hazy environments are prone to color distortion and low contrast;thus,the desired visual effect cannot be achieved and the difficulty of target detection is increased.Artificial intelligence(AI)solutions provide great help for dehazy images,which can automatically identify patterns or monitor the environment.Therefore,we propose a 3D reconstruction method of dehazed images for smart cities based on deep learning.First,we propose a fine transmission image deep convolutional regression network(FT-DCRN)dehazing algorithm that uses fine transmission image and atmospheric light value to compute dehazed image.The DCRN is used to obtain the coarse transmission image,which can not only expand the receptive field of the network but also retain the features to maintain the nonlinearity of the overall network.The fine transmission image is obtained by refining the coarse transmission image using a guided filter.The atmospheric light value is estimated according to the position and brightness of the pixels in the original hazy image.Second,we use the dehazed images generated by the FT-DCRN dehazing algorithm for 3D reconstruction.An advanced relaxed iterative fine matching based on the structure from motion(ARI-SFM)algorithm is proposed.The ARISFM algorithm,which obtains the fine matching corner pairs and reduces the number of iterations,establishes an accurate one-to-one matching corner relationship.The experimental results show that our FT-DCRN dehazing algorithm improves the accuracy compared to other representative algorithms.In addition,the ARI-SFM algorithm guarantees the precision and improves the efficiency.

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.

Real-Time Characterization of Crystal Shape and Size Distribution Based on Moving Window and 3D Imaging in a Stirred Tank

Crystal shape distribution, i.e. the multidimensional size distribution of crystals, is of great importance to their down-stream processing such as in filtration as well as to the end-use properties including the dissolution rate and bioavailability for crystalline pharmaceuticals. Engineering crystal shape and shape distribution requires knowledge about the growth behavior of different crystal facets under varied operational conditions e.g. supersaturations. Measurement of the facet growth rates and growth kinetics of static crystals in a crystallizer without stirring has been reported previously. Here attention is given to study on real-time characterization of the 3D facet growth behavior of crystals in a stirred tank where crystals are constantly moving and rotating. The measurement technique is stereo imaging and the crystal shape reconstruction is based on a stereo imaging camera model. By reference to a case study on potash alum crystallization, it is demonstrated that the crystal size and shape distributions (CSSD) of moving and rotating potash alum crystals in the solution can be reconstructed. The moving window approach was used to correlate 3D face growth kinetics with supersaturation (in the range 0.04 - 0.12) given by an ATR FTIR probe. It revealed that {100} is the fastest growing face, leading to a rapid reduction of its area, while the {111} face has the slowest growth rate, reflected in its area continuously getting larger.

A 3D Model Reconstruction Method Using Slice Images

Abstract：reconstruction method using slice im-ages is proposed. Wanting to extract the outermost contours from slice images, the method of the improved GVF-Snake model with optimized force field and ray method is employed. And then, the 3D model is reconstructed by contour connection using the im-proved shortest diagonal method and judgment function of contour fracture. The results show that the accuracy of reconstruction 3D model is improved.

Dynamic 3D shape reconstruction under complex reflection and transmission conditions using multi-scale parallel single-pixel imaging

Depth measurement and three-dimensional(3D)imaging under complex reflection and transmission conditions are challenging and even impossible for traditional structured light techniques,owing to the precondition of point-to-point triangulation.Despite recent progress in addressing this problem,there is still no efficient and general solution.Herein,a Fourier dual-slice projection with depth-constrained localization is presented to separate and utilize different illumination and reflection components efficiently,which can significantly decrease the number of projection patterns in each sequence from thousands to fifteen.Subsequently,multi-scale parallel single-pixel imaging(MS-PSI)is proposed based on the established and proven position-invariant theorem,which breaks the local regional assumption and enables dynamic 3D reconstruction.Our methodology successfully unveils unseen-before capabilities such as(1)accurate depth measurement under interreflection and subsurface scattering conditions,(2)dynamic measurement of the time-varying high-dynamic-range scene and through thin volumetric scattering media at a rate of 333 frames per second;(3)two-layer 3D imaging of the semitransparent surface and the object hidden behind it.The experimental results confirm that the proposed method paves the way for dynamic 3D reconstruction under complex optical field reflection and transmission conditions,benefiting imaging and sensing applications in advanced manufacturing,autonomous driving,and biomedical imaging.

Vertebrae CT Images 3D Reconstruction with Improve Marching Cubes Algorithm

Medical images 3D reconstruction is an important part in medical image analysis and processing. Although lots of algorithms have been proposed continuously, speed and accuracy cannot conform to actual needs, which has always been the focus topic. In this paper, we propose an Improved Marching Cubes algorithm ( I-MC) based on the surface rendering theory, which implements 3D reconstruction of the vertebrae. Firstly, we preprocessed the original 2D vertebrae CT images with the bilateral-filter denoising algorithm. Secondly, on the basis of the traditional Marching Cubes algorithm, the seed voxels were extracted and the Region Growing algorithm was used to determine all voxels that contain isosurfaces. Then, the Golden Section instead of the traditional linear interpolation was used to calculate the equivalent point, and this method reduced the calculations of public edges. VTK and OpenGL implemented 3D reconstruction of the vertebrae on GPU quickly and accurately. The experimental results show that when compared with the traditional Marching Cubes algorithm and Mesh Simplification Marching Cubes algorithm, the improved algorithm achieves a significant improvement of reconstruction speed while preserving the accurate results. The efficiency of algorithm is improved dramatically. This method is real-time and achieves the goal of efficient 3D reconstruction of vertebrae CT images.

3D Confocal Raman Imaging of Oil-Rich Emulsion from Enzyme-Assisted Aqueous Extraction of Extruded Soybean Powder

The understanding of the structure morphology of oil-rich emulsion from enzyme-assisted extraction processing(EAEP)was a critical step to break the oil-rich emulsion structure in order to recover oil.Albeit EAEP method has been applied as an alternative way to conventional solvent extraction method,the structure morphology of oil-rich emulsion was still unclear.The current study aimed to investigate the structure morphology of oil-rich emulsion from EAEP using 3 D confocal Raman imaging technique.With increasing the enzymatic hydrolysis duration from 1 to 3 h,the stability of oil-rich emulsion was decreased as visualized in the 3 D confocal Raman images that the protein and oil were mixed together.The subsequent Raman spectrum analysis further revealed that the decreased stability of oil-rich emulsion was due to the protein aggregations via SS bonds or protein-lipid interactions.The conformational transfer in protein indicated the formation of a compact structure.

基于CT图像重建人体膝关节3D骨骼优化模型

目的:重建一个含有股骨远端和胫骨近端的人体膝关节3D骨骼优化模型。方法:采用螺旋CT机扫描人体膝关节部位,从胫骨近端到股骨远端,获得DICOM格式图像数据。利用Mimics软件进行图像数据输入和视图图像处理重建3D骨骼模型,并使用它自带的3-matic软件对所建的3D模型进行优化处理。结果:使用Mimics软件重建了一个含有股骨远端和胫骨近端的左侧人体膝关节3D骨骼模型,其自带的3-matic软件重建了一个含有股骨远端和胫骨近端的左侧人体膝关节3D骨骼优化模型。结论:该优化模型可清晰精确地模拟股骨远端和胫骨近端的三维几何形态,能导入到ANSYS/ABAQUS等有限元软件进行力学特性分析,也能结合MRI重建含有半月板的人体膝关节生物力学模型,为仿生膝关节的结构设计提供理论依据。

CT三维重建配合3D打印技术在辅助寰枢椎椎弓根螺钉置入的应用价值评估

目的:探讨CT三维重建配合3D打印技术在辅助寰枢椎椎弓根螺钉置入的应用价值。方法:通过CT三维重建的多种后处理技术明确寰枢椎病变13例作为观察组,再将CT三维重建、逆向工程原理及快速成形技术相结合,设计出一种新型的导航模板,辅助椎弓根螺钉置入,并与13例之前已通过X线透视置钉法的病例(对照组)进行置钉效果比较。结果:对照组13例共置椎弓根螺钉41枚,其中Ⅰ类置钉9枚,Ⅱ类置钉18枚,Ⅲ类置钉14枚,成功率65.9%;观察组共打印颈椎模型13例,设计导向模板21个,5例由于先前通过X线透视仅在枢椎两侧的椎弓根内置钉,只制作出枢椎的导航模板;模拟手术同样置钉41枚,其中Ⅰ类置钉15枚,Ⅱ类置钉21枚,Ⅲ类置钉5枚,成功率87.8%。结论:CT三维重建的各种后处理技术不仅能够准确的判断寰枢椎病变,并能配合3D打印技术,制作出个体化的导航模板,使上颈椎椎弓根螺钉的置入变得既安全又省时,并能在术后准确评估置钉效果。

32×32 Si盖革模式激光焦平面探测器

为了满足350 nm~1100 nm波长范围内远距离及微弱激光3维成像探测的需求,提出了一种规模为32×32的盖革模式硅激光焦平面阵列探测器,它主要由硅雪崩光电二极管阵列、读出电路芯片、微透镜阵列、半导体制冷器、引脚网格阵列壳体等元件组成。硅雪崩光电二极管焦平面阵列采用拉通型N^(+)-Π_(1)-P^(-)-Π_(2)-P^(+)结构,工作在盖革模式下,通过Si片背面抛磨减薄及盲孔刻蚀技术,实现了纤薄光敏区的加工;读出电路采用主动模式淬灭设计,使电路单元的死时间控制在50 ns以内,并利用一种带相移技术的时间数字转换电路优化方案,在满足时间分辨率不大于2 ns的同时,降低了读出电路芯片的功耗。结果表明,在反向过偏电压14 V、工作温度-40℃的条件下,该探测器在850 nm的目标波长可实现20.7%的平均光子探测效率与0.59 kHz的平均暗计数率,时间分辨率为1 ns,有效像元率优于97%。该研究为纤薄型背进光Si基激光焦平面探测器的研制提供了参考。

Preliminary results of a Compton camera based on a single 3D position-sensitive CZT detector

A Compton camera prototype has been developed using a pixelated CZT detector with 4-by-4 pixels.Signals of the detector are read out by a VASTAT ASIC that is controlled by a self-developed DAQ board. The DAQ software is developed using LabVIEW, and the offline Compton imaging codes are written in C++. The prototype has been successfully calibrated, and its capabilities for source detection, spectroscopy, and Compton imaging have been demonstrated using a Cs-137 source.The angular resolution of the 662 keV line is 36° FWHM for the simple back-projection method and 9.6° FWHM for the MLEM reconstruction method. The system is ready to be extended to 11-by-11 pixels in the future, and a better imaging quality can be expected due to the better relative position resolution.

Single-cell volumetric imaging with light field microscopy: Advances in systems and algorithms

Single-cell volumetric imaging is essential for researching individual characteristics of cells.As a nonscanning imaging technique,lighteld microscopy(LFM)is a critical tool to achieve realtime three-dimensional imaging with the advantage of single-shot.To address the inherent limits including nonuniform resolution and block-wise artifacts,various modied LFM strategies have been developed to provide new insights into the structural and functional information of cells.This review will introduce the principle and development of LFM,discuss the improved approaches based on hardware designs and 3D reconstruction algorithms,and present the applications in single-cell imaging.

Segmentation-aided phase unwrapping for 3D reconstruction with airborne array-InSAR images

Unmanned aerial vehicle(UAV)array InSAR is a new type of single-flight 3D SAR imaging system with the advantages of high coherence and resolution.However,due to the low altitude of the platform,the elevation ambiguity of the system is smaller than the maximal terrain elevation.Since the spatial phase unwrapping is conducted based on the assumption of phase continuity,the inappropriate ambiguity will cause significant unwrapping errors.In this work,a 3D phase unwrapping algorithm assisted by image segmentation is proposed to address this issue.The Markov random field(MRF)is utilized for image segmentation.The optimal spatial phase unwrapping network is achieved based on the segmentation results.The asymptotic 3D phase unwrapping is adopted to get the refined 3D reconstruction.Results based on the real airborne array-InSAR data show that the proposed method effectively improves the elevation ambiguity.

3D visualization of the material flow in friction stir welding process

The material flow in friction stir welded 2014 Al alloy has been investigated using a marker insert technique （MIT）. Results of the flow visualization show that the material flow is asymmetrical during the friction stir welding （FSW） process and there are also significant differences in the flow patterns observed on advancing side and retreating side. On advancing side, some material transport forward and some move backward, but on retreating side, material only transport backward. At the top surface of the weld, significant material transport forward due to the action of the rotating tool shoulder. Combining the data from all the markers, a three-dituensional flow visualization, similar to the 3D image reconstruction technique, was obtained. The three-dimensional plot gives the tendency chart of material flow in friction stir welding process and from the plot it can be seen that there is a vertical, circular motion around the longitudinal axis of the weld. On the advancing side of the weld, the material is pushed downward but on the retreating side, the material is pushed toward the crown of the weld. The net result of the two relative motions in both side of the advancing and the retreating is that a circular motion comes into being. Comparatively, the material flow around the longitudinal axis is a secondary motion.