Efficient single-pixel imaging encrypted transmission based on 3D Arnold transformation

Single-pixel imaging(SPI)can transform 2D or 3D image data into 1D light signals,which offers promising prospects for image compression and transmission.However,during data communication these light signals in public channels will easily draw the attention of eavesdroppers.Here,we introduce an efficient encryption method for SPI data transmission that uses the 3D Arnold transformation to directly disrupt 1D single-pixel light signals and utilizes the elliptic curve encryption algorithm for key transmission.This encryption scheme immediately employs Hadamard patterns to illuminate the scene and then utilizes the 3D Arnold transformation to permutate the 1D light signal of single-pixel detection.Then the transformation parameters serve as the secret key,while the security of key exchange is guaranteed by an elliptic curve-based key exchange mechanism.Compared with existing encryption schemes,both computer simulations and optical experiments have been conducted to demonstrate that the proposed technique not only enhances the security of encryption but also eliminates the need for complicated pattern scrambling rules.Additionally,this approach solves the problem of secure key transmission,thus ensuring the security of information and the quality of the decrypted images.

Geant4 simulation of fast-electron bremsstrahlung imaging at the HL-3 tokamak

To further research on high-parameter plasma,we plan to develop a two-dimensional hard X-ray(HXR)imaging system at the HL-3 tokamak to measure HXRs with energies ranging from 20 to 300 keV.The application of an array-structured detector ensures that this system can measure HXR-radiation spectra from the entire plasma cross section.Therefore,it is suitable for the study of fast-electron physics,such as radio-frequency wave current drives,fast electrons driving instabilities,and plasma disruptions in fusion research.In this study,we develop a simulation for calculating fast-electron bremsstrahlung in the HL-3 tokamak based on the Monte Carlo simulation code Geant4,in which the plasma geometry and forward scattering of fast-electron bremsstrahlung are considered.The preliminary calculation results indicate that the HXR energy deposi-tion on the detector is symmetrically distributed,even though the plasma distribution is asymmetric owing to the toroidal effect.These simulation results are helpful in constructing the relationship between the energy deposition on the detector and parameter distribution on the plasma cross section during HL-3 experiments.This is beneficial for the reconstruction of the fast-electron-distribution function and for optimizing the design of the HXR-imaging system.

MACS-W:A modified optical clearing agent for imaging 3D cell cultures

Three-dimensional(3D)cell cultures have contributed to a variety of biological research fields by filling the gap between monolayers and animal models.The modern optical sectioning microscopic methods make it possible to probe the complexity of 3D cell cultures but are limited by the inherent opaqueness.While tissue optical clearing methods have emerged as powerful tools for investigating whole-mount tissues in 3D,they often have limitations,such as being too harsh for fragile 3D cell cultures,requiring complex handling protocols,or inducing tissue deformation with shrinkage or expansion.To address this issue,we proposed a modified optical clearing method for 3D cell cultures,called MACS-W,which is simple,highly efficient,and morphology-preserving.In our evaluation of MACS-W,we found that it exhibits excellent clearing capability in just 10 min,with minimal deformation,and helps drug evaluation on tumor spheroids.In summary,MACS-W is a fast,minimally-deformative and fluorescence compatible clearing method that has the potential to be widely used in the studies of 3D cell cultures.

A Tabletop Nano-CT Image Noise Reduction Network Based on 3-Dimensional Axial Attention Mechanism

Nano-computed tomography(Nano-CT)is an emerging,high-resolution imaging technique.However,due to their low-light properties,tabletop Nano-CT has to be scanned under long exposure conditions,which the scanning process is time-consuming.For 3D reconstruction data,this paper proposed a lightweight 3D noise reduction method for desktop-level Nano-CT called AAD-ResNet(Axial Attention DeNoise ResNet).The network is framed by theU-net structure.The encoder and decoder are incorporated with the proposed 3D axial attention mechanism and residual dense block.Each layer of the residual dense block can directly access the features of the previous layer,which reduces the redundancy of parameters and improves the efficiency of network training.The 3D axial attention mechanism enhances the correlation between 3D information in the training process and captures the long-distance dependence.It can improve the noise reduction effect and avoid the loss of image structure details.Experimental results show that the network can effectively improve the image quality of a 0.1-s exposure scan to a level close to a 3-s exposure,significantly shortening the sample scanning time.

Magnetic resonance imaging combined with serum endolipin and galactagoglobin-3 to diagnose cerebral infarction in the elderly with diabetes mellitus

BACKGROUND Magnetic resonance imaging(MRI)combined with serum endothelin and galactagoglobin-3(Gal-3)can improve the clinical diagnosis of diabetes mellitus complicated with cerebral infarction.AIM To analyze the clinical value of MRI combined with serum endolipin and Gal-3 for the diagnosis of cerebral infarction in the elderly with diabetes mellitus.METHODS One hundred and fifty patients with acute cerebral infarction hospitalized between January 2021 and December 2023 were divided into two groups according to comorbid diabetes mellitus,including 62 and 88 cases in the diabetic and nondiabetic cerebral infarction groups.Serum samples were collected to detect the expression of serum endolipoxins,and Gal-3,and cranial MRI was performed at admission.Differences between the two groups were compared to analyze the diagnostic value of these parameters.RESULTS Serum endolipin and Gal-3 expression were higher in the diabetic cerebral infarction group(P<0.05).The arterial wall area,vessel area,normalized wall index,and lumen stenosis rate were higher in the diabetic cerebral infarction group,while the rate of arterial lumen moderate and severe stenosis was 48.39% higher(36.36%,P<0.05).The percentage of large(29.03%)and multiple infarcts(33.87%)in the diabetic cerebral infarction group was higher(13.64% and 20.45%),and the incidence rate of lacunar infarcts was lower(37.10%vs 65.91%)(P<0.05).The total incidence of arterial plaque in patients in the diabetic cerebral infarction group was 96.77% higher(69.32%),while the incidence of necrotic lipid core plaque was 58.06%higher(26.14%)(P<0.05).Receiver operating characteristic curve analysis was performed to assess the diagnosis utility of these techniques.MRI in combination with serum endoglin and Gal-3 had the highest area under the curve,the Yoden index,sensitivity and specificity(P<0.05).CONCLUSION The expression of serum endolipin and Gal-3 in elderly patients with diabetes mellitus with cerebral infarction showed an elevated trend,and the degree of luminal stenosis was severe.MRI predominantly revealed large and multiple infarct foci.This combined index examination can improve the clinical diagnosis of diabetes mellitus combined with cerebral infarction.

Correg-Yolov3:a Method for Dense Buildings Detection in High-resolution Remote Sensing Images

The exploration of building detection plays an important role in urban planning,smart city and military.Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resolution remote sensing images,we present an effective YOLOv3 framework,corner regression-based YOLOv3(Correg-YOLOv3),to localize dense building accurately.This improved YOLOv3 algorithm establishes a vertex regression mechanism and an additional loss item about building vertex offsets relative to the center point of bounding box.By extending output dimensions,the trained model is able to output the rectangular bounding boxes and the building vertices meanwhile.Finally,we evaluate the performance of the Correg-YOLOv3 on our self-produced data set and provide a comparative analysis qualitatively and quantitatively.The experimental results achieve high performance in precision(96.45%),recall rate(95.75%),F1 score(96.10%)and average precision(98.05%),which were 2.73%,5.4%,4.1%and 4.73%higher than that of YOLOv3.Therefore,our proposed algorithm effectively tackles the problem of dense building detection in high resolution images.

Non-invasively differentiate non-alcoholic steatohepatitis by visualizing hepatic integrinαvβ3 expression with a targeted molecular imaging modality

BACKGROUND Non-invasive methods to diagnose non-alcoholic steatohepatitis(NASH),an inflammatory subtype of non-alcoholic fatty liver disease(NAFLD),are currently unavailable.AIM To develop an integrinαvβ3-targeted molecular imaging modality to differentiate NASH.METHODS Integrinαvβ3 expression was assessed in Human LO2 hepatocytes Scultured with palmitic and oleic acids(FFA).Hepatic integrinαvβ3 expression was analyzed in rabbits fed a high-fat diet(HFD)and in rats fed a high-fat,high-carbohydrate diet(HFCD).After synthesis,cyclic arginine-glycine-aspartic acid peptide(cRGD)was labeled with gadolinium(Gd)and used as a contrast agent in magnetic resonance imaging(MRI)performed on mice fed with HFCD.RESULTS Integrinαvβ3 was markedly expressed on FFA-cultured hepatocytes,unlike the control hepatocytes.Hepatic integrinαvβ3 expression significantly increased in both HFD-fed rabbits and HFCD-fed rats as simple fatty liver(FL)progressed to steatohepatitis.The distribution of integrinαvβ3 in the liver of NASH cases largely overlapped with albumin-positive staining areas.In comparison to mice with simple FL,the relative liver MRI-T1 signal value at 60 minutes post-injection of Gd-labeled cRGD was significantly increased in mice with steatohepatitis(P<0.05),showing a positive correlation with the NAFLD activity score(r=0.945;P<0.01).Hepatic integrinαvβ3 expression was significantly upregulated during NASH development,with hepatocytes being the primary cells expressing integrinαvβ3.CONCLUSION After using Gd-labeled cRGD as a tracer,NASH was successfully distinguished by visualizing hepatic integrinαvβ3 expression with MRI.

The Application of Digital Optical 3D Image Analyzer Evaskin in The Evaluation of Wrinkles

To verify the effectiveness of digital optical 3D image analyzer EvaSKIN in the objective and quantitative evaluation of wrinkles.A total of 115 subjects were recruited,the facial images of the subjects were collected by digital optical 3D image analyzer and manual camera,the changes of crow’s feet with age were analyzed.Pictures obtained by manual photography can be directly used for observation and preliminary grading of wrinkles.However,the requirements for evaluators are high,and the results are prone to errors,which will affect the accuracy of the evaluation.Therefore,skilled raters are needed.Compared with the manual photography method,the digital optical 3D image analyzer EvaSKIN can realize three-dimensional extraction of wrinkles,and obtain the change trend of crow’s feet with age.20~30 years old,wrinkles begin to appear slowly;wrinkles will increase rapidly at the age of 30~50;The length of 50~60 year old wrinkles is basically fixed,the wrinkles develop longitudewise,gradually widen and deepen,and the area,depth and volume increase is obvious,and the skin aging condition is intensified.the digital optical 3D image analyzer EvaSKIN realizes the 3D extraction of wrinkles,quantifies the circumference,area,average depth,maximum depth and volume of wrinkles,realizes the objective and quantitative evaluation of wrinkle state,is more accurate in the measurement of wrinkles,and provides a new instrument and method for the evaluation of wrinkles.it is a perfect and supplement to the traditional evaluation methods,and to a certain extent,it helps the research and development and evaluation institutions of cosmetics to obtain more abundant and three-dimensional data support.

The Application Value of Ultrasound Imaging in the Differential Diagnosis of Benign and Malignant Breast Nodules of BI-RADS 3 and Above

Objective:To explore the diagnostic value of ultrasound imaging for breast nodules of breast imaging-reporting and data system(BI-RADS)category 3 and above.Methods:From June 2021 to July 2022,163 patients with breast nodules of BI-RADS 3 or above were selected as the research subjects.After pathological diagnosis,24 cases were malignant breast nodules of BI-RADS 3 or above,while 139 cases were benign breast nodules of BI-RADS 3 or above.The diagnosis rate of malignant and benign breast nodules of BI-RADS 3 or above,including 95%CI,was observed and analyzed.Results:The malignant and benign detection rates of conventional ultrasound were 88.63%and 75.00%,respectively,and the malignant and benign detection rates of ultrasound imaging were 93.18%and 87.50%,respectively,with 95%CIs greater than 0.7.Conclusion:Ultrasound imaging can help improve the diagnostic accuracy of benign and malignant breast nodules of BI-RADS 3 and above and reduce the misdiagnosis rate.

An Improved High Precision 3D Semantic Mapping of Indoor Scenes from RGB-D Images

This paper proposes an improved high-precision 3D semantic mapping method for indoor scenes using RGB-D images.The current semantic mapping algorithms suffer from low semantic annotation accuracy and insufficient real-time performance.To address these issues,we first adopt the Elastic Fusion algorithm to select key frames from indoor environment image sequences captured by the Kinect sensor and construct the indoor environment space model.Then,an indoor RGB-D image semantic segmentation network is proposed,which uses multi-scale feature fusion to quickly and accurately obtain object labeling information at the pixel level of the spatial point cloud model.Finally,Bayesian updating is used to conduct incremental semantic label fusion on the established spatial point cloud model.We also employ dense conditional random fields(CRF)to optimize the 3D semantic map model,resulting in a high-precision spatial semantic map of indoor scenes.Experimental results show that the proposed semantic mapping system can process image sequences collected by RGB-D sensors in real-time and output accurate semantic segmentation results of indoor scene images and the current local spatial semantic map.Finally,it constructs a globally consistent high-precision indoor scenes 3D semantic map.

Short‐term and long‐term memory self‐attention network for segmentation of tumours in 3D medical images

Tumour segmentation in medical images(especially 3D tumour segmentation)is highly challenging due to the possible similarity between tumours and adjacent tissues,occurrence of multiple tumours and variable tumour shapes and sizes.The popular deep learning‐based segmentation algorithms generally rely on the convolutional neural network(CNN)and Transformer.The former cannot extract the global image features effectively while the latter lacks the inductive bias and involves the complicated computation for 3D volume data.The existing hybrid CNN‐Transformer network can only provide the limited performance improvement or even poorer segmentation performance than the pure CNN.To address these issues,a short‐term and long‐term memory self‐attention network is proposed.Firstly,a distinctive self‐attention block uses the Transformer to explore the correlation among the region features at different levels extracted by the CNN.Then,the memory structure filters and combines the above information to exclude the similar regions and detect the multiple tumours.Finally,the multi‐layer reconstruction blocks will predict the tumour boundaries.Experimental results demonstrate that our method outperforms other methods in terms of subjective visual and quantitative evaluation.Compared with the most competitive method,the proposed method provides Dice(82.4%vs.76.6%)and Hausdorff distance 95%(HD95)(10.66 vs.11.54 mm)on the KiTS19 as well as Dice(80.2%vs.78.4%)and HD95(9.632 vs.12.17 mm)on the LiTS.

A network lightweighting method for difficult segmentation of 3D medical images

Currently,deep learning is widely used in medical image segmentation and has achieved good results.However,3D medical image segmentation tasks with diverse lesion characters,blurred edges,and unstable positions require complex networks with a large number of parameters.It is computationally expensive and results in high requirements on equipment,making it hard to deploy the network in hospitals.In this work,we propose a method for network lightweighting and applied it to a 3D CNN based network.We experimented on a COVID-19 lesion segmentation dataset.Specifically,we use three cascaded one-dimensional convolutions to replace a 3D convolution,and integrate instance normalization with the previous layer of one-dimensional convolutions to accelerate network inference.In addition,we simplify test-time augmentation and deep supervision of the network.Experiments show that the lightweight network can reduce the prediction time of each sample and the memory usage by 50%and reduce the number of parameters by 60%compared with the original network.The training time of one epoch is also reduced by 50%with the segmentation accuracy dropped within the acceptable range.

3D characterization and analysis of pore structure of packed ore particle beds based on computed tomography images

Methods and procedures of three-dimensional （3D） characterization of the pore structure features in the packed ore particle bed are focused. X-ray computed tomography was applied to deriving the cross-sectional images of specimens with single particle size of 1-2, 2-3, 3-4, 4-5, 5-6, 6-7, 7-8, 8-9, 9-10 ram. Based on the in-house developed 3D image analysis programs using Matlab, the volume porosity, pore size distribution and degree of connectivity were calculated and analyzed in detail. The results indicate that the volume porosity, the mean diameter of pores and the effective pore size （d50） increase with the increasing of particle size. Lognormal distribution or Gauss distribution is mostly suitable to model the pore size distribution. The degree of connectivity investigated on the basis of cluster-labeling algorithm also increases with increasing the particle size approximately.

MRI T_2 star mapping、T_1 images与3D DESS融合图在隐匿性膝关节软骨损伤中的应用

目的探讨T_2 star mapping、T_1 images与3D DESS融合伪彩图在关节软骨损伤中的诊断价值。方法对26例关节软骨损伤患者行T_2 star mapping、T_1 images和3D DESS扫描,并将T_1 images、T_2 star mapping与3D DESS图像融合,评价患者股骨、胫骨、髌骨关节软骨损伤程度并与关节镜结果对比,计算融合伪彩图诊断软骨损伤的特异性、敏感性及与关节镜诊断结果一致性。结果 T_1 images-3D DESS融合伪彩图诊断关节软骨损伤的敏感度、特异度及Kappa值分别为92.8%、93.0%、0.769,T_2 star mapping-3D DESS融合伪彩图诊断关节软骨损伤的敏感度、特异度及Kappa值分别为91.4%、94.2%、0.787。结论 T_2 star mapping、T_1 images与3D DESS融合伪彩图在关节软骨早期损伤评价上优于关节镜。

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。

Novel registration algorithm for 3-D images captured from multiple views of object surface

A novel algorithm of 3-D surface image registration is proposed. It makes use of the array information of 3-D points and takes vector/vertex-like features as the basis of the matching. That array information of 3-D points can be easily obtained when capturing original 3-D images. The iterative least-mean-squared （LMS） algorithm is applied to optimizing adaptively the transformation matrix parameters. These can effectively improve the registration performance and hurry up the matching process. Experimental results show that it can reach a good subjective impression on aligned 3-D images. Although the algorithm focuses primarily on the human head model, it can also be used for other objects with small modifications.

2 cm以上的C-TI-RADS 3类甲状腺结节的临床特点分析

目的统计2 cm以上的中国版甲状腺影像报告及数据系统(C-TI-RADS)3类甲状腺结节的临床特点,并探究其与性别、结节成分、对侧是否有癌、是否弥漫性回声改变、甲状腺过氧化物酶抗体(thyroid peroxidase antibody,TPOAB)、甲状腺球蛋白抗体(anti-thyroglobulin antibodies,TGAB)等的相关性。方法回顾性分析2022年9月-2023年3月我科收治的甲状腺超声C-TI-RADS 3类且最大直径≥2 cm的94例甲状腺结节患者(均接受细胞病理和/或组织病理检查)的临床病理学信息。统计TBSⅠ类、良性、低风险肿瘤、恶性的比例,并比较性别、结节成分、对侧是否有癌、是否弥漫性回声改变、TPOAB、TGAB等临床特点在良性、低风险肿瘤、恶性三组中的比例有无统计学差异。结果排除7例TBSⅠ类患者,87例结节病理明确患者中,良性72例(细胞学38例、组织学34例)、低风险肿瘤5例(细胞学2例、组织学3例)、恶性10例(PTC 8例、FTC 1例、MTC 1例)。不同病理类型之间,结节成分(囊实性/实性)组间差异具有显著性,差异有统计学意义(χ^(2)=10.369,P=0.006);性别、是否弥漫性回声改变、对侧是否有癌、TPOAB、TGAB组间差异无统计学意义(P均>0.05)。进一步分析结节成分与病理类型的关系,结果表明,低风险肿瘤相对于良性结节实性比例更高,差异有统计学意义(χ^(2)=9.571,P=0.002);而恶性结节相对于低风险肿瘤(χ^(2)=2.143,P=0.143),恶性结节相对于良性结节(χ^(2)=2.165,P=0.141)囊实性比例差异均无统计学意义。结论虽然各种版本的甲状腺影像报告与数据系统均将TI-RADS 3级结节认定为良性可能,但恶性结节在C-TI-RADS 3类甲状腺结节中仍占一定比例,需要重视诸如囊实性结节、甲状腺滤泡性肿瘤、甲状腺髓样癌等超声征象不典型的甲状腺结节。在评估结节良恶性时,超声引导下细针穿刺细胞病理学检查是必要的,需要重视标本不满意或无法诊断的情况,提高诊断的准确性。

3D imaging lipidometry in single cell by in-flow holographic tomography

The most recent discoveries in the biochemical field are highlighting the increasingly important role of lipid droplets(LDs)in several regulatory mechanisms in living cells.LDs are dynamic organelles and therefore their complete characterization in terms of number,size,spatial positioning and relative distribution in the cell volume can shed light on the roles played by LDs.Until now,fluorescence microscopy and transmission electron microscopy are assessed as the gold standard methods for identifying LDs due to their high sensitivity and specificity.However,such methods generally only provide 2D assays and partial measurements.Furthermore,both can be destructive and with low productivity,thus limiting analysis of large cell numbers in a sample.Here we demonstrate for the first time the capability of 3D visualization and the full LD characterization in high-throughput with a tomographic phase-contrast flow-cytometer,by using ovarian cancer cells and monocyte cell lines as models.A strategy for retrieving significant parameters on spatial correlations and LD 3D positioning inside each cell volume is reported.The information gathered by this new method could allow more in depth understanding and lead to new discoveries on how LDs are correlated to cellular functions.

Integral imaging-based tabletop light field 3D display with large viewing angle

Light field 3D display technology is considered a revolutionary technology to address the critical visual fatigue issues in the existing 3D displays.Tabletop light field 3D display provides a brand-new display form that satisfies multi-user shared viewing and collaborative works,and it is poised to become a potential alternative to the traditional wall and portable display forms.However,a large radial viewing angle and correct radial perspective and parallax are still out of reach for most current tabletop light field 3D displays due to the limited amount of spatial information.To address the viewing angle and perspective issues,a novel integral imaging-based tabletop light field 3D display with a simple flat-panel structure is proposed and developed by applying a compound lens array,two spliced 8K liquid crystal display panels,and a light shaping diffuser screen.The compound lens array is designed to be composed of multiple three-piece compound lens units by employing a reverse design scheme,which greatly extends the radial viewing angle in the case of a limited amount of spatial information and balances other important 3D display parameters.The proposed display has a radial viewing angle of 68.7°in a large display size of 43.5 inches,which is larger than the conventional tabletop light field 3D displays.The radial perspective and parallax are correct,and high-resolution 3D images can be reproduced in large radial viewing positions.We envision that this proposed display opens up possibility for redefining the display forms of consumer electronics.

Anisotropic creep behavior of soft-hard interbedded rock masses based on 3D printing and digital imaging correlation technology

Three-dimensional(3D)printing technology is increasingly used in experimental research of geotechnical engineering.Compared to other materials,3D layer-by-layer printing specimens are extremely similar to the inherent properties of natural layered rock masses.In this paper,soft-hard interbedded rock masses with different dip angles were prepared based on 3D printing(3DP)sand core technology.Uniaxial compression creep tests were conducted to investigate its anisotropic creep behavior based on digital imaging correlation(DIC)technology.The results show that the anisotropic creep behavior of the 3DP soft-hard interbedded rock mass is mainly affected by the dip angles of the weak interlayer when the stress is at low levels.As the stress level increases,the effect of creep stress on its creep anisotropy increases significantly,and the dip angle is no longer the main factor.The minimum value of the long-term strength and creep failure strength always appears in the weak interlayer within 30°–60°,which explains why the failure of the layered rock mass is controlled by the weak interlayer and generally emerges at 45°.The tests results are verified by comparing with theoretical and other published studies.The feasibility of the 3DP soft-hard interbedded rock mass provides broad prospects and application values for 3DP technology in future experimental research.