Evaluation of mitral chordae tendineae length using four-dimensional computed

BACKGROUND Mitral valvuloplasty using artificial chordae tendineae represents an effective surgical approach for treating mitral regurgitation.Achieving precise measurements of artificial chordae tendineae length(CL)is an important factor in the procedure;however,no objective index currently exists to facilitate this measurement.Therefore,preoperative assessment of CL is critical for surgical planning and support.Four-dimensional x-ray micro-computed tomography(4D-CT)may be useful for accurate CL measurement considering that it allows for dynamic three-dimensional(3D)evaluation compared to that with transthoracic echocardiography,a conventional inspection method.AIM To investigate the behavior and length of mitral chordae tendineae during systole using 4D-CT.METHODS Eleven adults aged>70 years without mitral valve disease were evaluated.A 64-slice CT scanner was used to capture 20 phases in the cardiac cycle in electrocardiographic synchronization.The length of the primary chordae tendineae was measured from early systole to early diastole using the 3D image.The primary chordae tendineae originating from the anterior papillary muscle and attached to the A1-2 region and those from the posterior papillary muscle and attached to the A2-3 region were designated as cA and cP,respectively.The behavior and maximum lengths[cA(ma),cP(max)]were compared,and the correlation with body surface area(BSA)was evaluated.RESULTS In all cases,the mitral anterior leaflet chordae tendineae could be measured.In most cases,the cA and cP chordae tendineae could be measured visually.The mean cA(max)and cP(max)were 20.2 mm±1.95 mm and 23.5 mm±4.06 mm,respectively.cP(max)was significantly longer.The correlation coefficients(r)with BSA were 0.60 and 0.78 for cA(max)and cP(max),respectively.Both cA and cP exhibited constant variation in CL during systole,with a maximum 1.16-fold increase in cA and a 1.23-fold increase in cP from early to mid-systole.For cP,CL reached a plateau at 15%and remained elongated until end-systole,whereas for cA,after peaking at 15%,CL shortened slightly and then moved toward its peak again as end-systole approached.CONCLUSION The study suggests that 4D-CT is a valuable tool for accurate measurement of both the length and behavior of chordae tendineae within the anterior leaflet of the mitral valve.

Recent progress in visualization and digitization of coherent transformation structures and application in high-strength steel

High-strength steels are mainly composed of medium-or low-temperature microstructures,such as bainite or martensite,with coherent transformation characteristics.This type of microstructure has a high density of dislocations and fine crystallographic structural units,which ease the coordinated matching of high strength,toughness,and plasticity.Meanwhile,given its excellent welding perform-ance,high-strength steel has been widely used in major engineering constructions,such as pipelines,ships,and bridges.However,visual-ization and digitization of the effective units of these coherent transformation structures using traditional methods(optical microscopy and scanning electron microscopy)is difficult due to their complex morphology.Moreover,the establishment of quantitative relationships with macroscopic mechanical properties and key process parameters presents additional difficulty.This article reviews the latest progress in microstructural visualization and digitization of high-strength steel,with a focus on the application of crystallographic methods in the development of high-strength steel plates and welding.We obtained the crystallographic data(Euler angle)of the transformed microstruc-tures through electron back-scattering diffraction and combined them with the calculation of inverse transformation from bainite or martensite to austenite to determine the reconstruction of high-temperature parent austenite and orientation relationship(OR)during con-tinuous cooling transformation.Furthermore,visualization of crystallographic packets,blocks,and variants based on actual OR and digit-ization of various grain boundaries can be effectively completed to establish quantitative relationships with alloy composition and key process parameters,thereby providing reverse design guidance for the development of high-strength steel.

Utility of real-time 3D visualization system in the early stage of phacoemulsification training

●AIM:To determine the teaching effects of a real-time three dimensional(3D)visualization system in the operating room for early-stage phacoemulsification training.●METHODS:A total of 10 ophthalmology residents of the first-year postgraduate were included.All the residents were novices to cataract surgery.Real-time cataract surgical observations were performed using a custom-built 3D visualization system.The training lasted 4wk(32h)in all.A modified International Council of Ophthalmology’s Ophthalmology Surgical Competency Assessment Rubric(ICO-OSCAR)containing 4 specific steps of cataract surgery was applied.The self-assessment(self)and expert-assessment(expert)were performed through the microsurgical attempts in the wet lab for each participant.●RESULTS:Compared with pre-training assessments(self 3.2±0.8,expert 2.5±0.6),the overall mean scores of posttraining(self 5.2±0.4,expert 4.7±0.6)were significantly improved after real-time observation training of 3D visualization system(P<0.05).Scores of 4 surgical items were significantly improved both self and expert assessment after training(P<0.05).●CONCLUSION:The 3D observation training provides novice ophthalmic residents with a better understanding of intraocular microsurgical techniques.It is a useful tool to improve teaching efficiency of surgical education.

The cardiovascular system at high altitude:A bibliometric and visualization analysis

BACKGROUND When exposed to high-altitude environments,the cardiovascular system undergoes various changes,the performance and mechanisms of which remain controversial.AIM To summarize the latest research advancements and hot research points in the cardiovascular system at high altitude by conducting a bibliometric and visualization analysis.METHODS The literature was systematically retrieved and filtered using the Web of Science Core Collection of Science Citation Index Expanded.A visualization analysis of the identified publications was conducted employing CiteSpace and VOSviewer.RESULTS A total of 1674 publications were included in the study,with an observed annual increase in the number of publications spanning from 1990 to 2022.The United States of America emerged as the predominant contributor,while Universidad Peruana Cayetano Heredia stood out as the institution with the highest publication output.Notably,Jean-Paul Richalet demonstrated the highest productivity among researchers focusing on the cardiovascular system at high altitude.Furthermore,Peter Bärtsch emerged as the author with the highest number of cited articles.Keyword analysis identified hypoxia,exercise,acclimatization,acute and chronic mountain sickness,pulmonary hypertension,metabolism,and echocardiography as the primary research hot research points and emerging directions in the study of the cardiovascular system at high altitude.CONCLUSION Over the past 32 years,research on the cardiovascular system in high-altitude regions has been steadily increasing.Future research in this field may focus on areas such as hypoxia adaptation,metabolism,and cardiopulmonary exercise.Strengthening interdisciplinary and multi-team collaborations will facilitate further exploration of the pathophysiological mechanisms underlying cardiovascular changes in high-altitude environments and provide a theoretical basis for standardized disease diagnosis and treatment.

Importance-aware 3D volume visualization for medical content-based image retrieval-a preliminary study

Background A medical content-based image retrieval(CBIR)system is designed to retrieve images from large imaging repositories that are visually similar to a user′s query image.CBIR is widely used in evidence-based diagnosis,teaching,and research.Although the retrieval accuracy has largely improved,there has been limited development toward visualizing important image features that indicate the similarity of retrieved images.Despite the prevalence of 3D volumetric data in medical imaging such as computed tomography(CT),current CBIR systems still rely on 2D cross-sectional views for the visualization of retrieved images.Such 2D visualization requires users to browse through the image stacks to confirm the similarity of the retrieved images and often involves mental reconstruction of 3D information,including the size,shape,and spatial relations of multiple structures.This process is time-consuming and reliant on users'experience.Methods In this study,we proposed an importance-aware 3D volume visualization method.The rendering parameters were automatically optimized to maximize the visibility of important structures that were detected and prioritized in the retrieval process.We then integrated the proposed visualization into a CBIR system,thereby complementing the 2D cross-sectional views for relevance feedback and further analyses.Results Our preliminary results demonstrate that 3D visualization can provide additional information using multimodal positron emission tomography and computed tomography(PETCT)images of a non-small cell lung cancer dataset.

Mapping the global research landscape on nonalcoholic fatty liver disease and insulin resistance:A visualization and bibliometric study

BACKGROUND Nonalcoholic fatty liver disease(NAFLD)is a liver condition that is prevalent worldwide and associated with significant health risks and economic burdens.As it has been linked to insulin resistance(IR),this study aimed to perform a bibliometric analysis and visually represent the scientific literature on IR and NAFLD.AIM To map the research landscape to underscore critical areas of focus,influential studies,and future directions of NAFLD and IR.METHODS This study conducted a bibliometric analysis of the literature on IR and NAFLD indexed in the SciVerse Scopus database from 1999 to 2022.The search strategy used terms from the literature and medical subject headings,focusing on terms related to IR and NAFLD.VOSviewer software was used to visualize research trends,collaborations,and key thematic areas.The analysis examined publication type,annual research output,contributing countries and institutions,funding agencies,journal impact factors,citation patterns,and highly cited references.RESULTS This analysis identified 23124 documents on NAFLD,revealing a significant increase in the number of publications between 1999 and 2022.The search retrieved 715 papers on IR and NAFLD,including 573(80.14%)articles and 88(12.31%)reviews.The most productive countries were China(n=134;18.74%),the United States(n=122;17.06%),Italy(n=97;13.57%),and Japan(n=41;5.73%).The leading institutions included the Universitàdegli Studi di Torino,Italy(n=29;4.06%),and the Consiglio Nazionale delle Ricerche,Italy(n=19;2.66%).The top funding agencies were the National Institute of Diabetes and Digestive and Kidney Diseases in the United States(n=48;6.71%),and the National Natural Science Foundation of China(n=37;5.17%).The most active journals in this field were Hepatology(27 publications),the Journal of Hepatology(17 publications),and the Journal of Clinical Endocrinology and Metabolism(13 publications).The main research hotspots were“therapeutic approaches for IR and NAFLD”and“inflammatory and high-fat diet impacts on NAFLD”.CONCLUSION This is the first bibliometric analysis to examine the relationship between IR and NAFLD.In response to the escalating global health challenge of NAFLD,this research highlights an urgent need for a better understanding of this condition and for the development of intervention strategies.Policymakers need to prioritize and address the increasing prevalence of NAFLD.

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.

Large-scale spatial data visualization method based on augmented reality

Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.

Exploring Digital Visualization Methods in Urban Public Building Space Design

Digital technology has driven the innovation of architectural design methods and tools,applying digital techniques to allow greater possibilities for more innovative and scientific design of public building spaces.This article first analyzes the characteristics of digital visualization and its advantages in the design of urban public building spaces,including aspects such as visualizing three-dimensional expression,rational analysis of building space,Virtual Reality Experience,and integration of design and construction processes.Subsequently,by introducing digital design methods such as parametric design,algorithmic generation,nonlinear design,and artificial intelligence-assisted design,it explores the methods and implementation approaches of digital visualization in the design of public building spaces.The aim is to offer insights and references for the deeper integration of digital technology into architectural design practices.

Research on Visualization and Interactive Design of Plant Configuration Virtual Reality in the Context of Digitalization

This study aims to explore the application of digital technology in landscape design,focusing on the research of virtual reality visualization and interactive design in the process of plant configuration.Through an in-depth analysis of digital technology,the study outlines its important role in landscape design,especially in the application of plant configuration.The current application status of virtual reality technology in landscape design is discussed,as well as how interactive design can enhance user experience and participation.Furthermore,the achievements and challenges of digital technology in landscape design are summarized.Finally,it proposes future research directions and suggestions,aiming to provide new ideas and methods for practice and research in the field of landscape design and promote the further application and development of digital technology in landscape design.

Traditional Chinese Medicine in colorectal cancer treatment:a bibliometrics study and visualization analysis via CiteSpace

Objective:To evaluate the current state of research and areas of interest for traditional Chinese medicine(TCM)in the field of colorectal cancer treatment.Methods:Related papers published between January 1,2012,and November 27,2021,were found using the Web of Science Core Collection Science Citation Index Expanded.Using CiteSpace's network map generation capability,we then determined the top writers,organizations,countries,keywords,co-cited writers,journals,references,and research trends.Results:This investigation yielded a total of 336 relevant papers.China is the most productive country.Shanghai University of Traditional Chinese Medicine is the leading institution.The journal with the most popularity and publishing volume is Evidence-based Complementary and Alternative Medicine.The author with the most citations and centrality is Lin JM.The terms"epithelial-mesenchymal transition,""cell cycle arrest,""apoptosis,"and"autophagy"are highly frequent and have a high betweenness centrality.Conclusion:According to the results,research on natural products,traditional Chinese medicine(TCM)extracts,and the molecular mechanisms of TCM chemical constituents constitutes the primary focus within TCM cancer treatment investigations.In recent years,there has been a surge of interest in exploring the role of gut microbiota in TCM chemical constituents research,particularly in its ability to induce apoptosis and autophagy in tumor cells,thereby suppressing tumor cell proliferation,metastasis,and invasion.However,due to the intricate composition of TCM and existing technical limitations,the underlying principles guiding TCM's efficacy in treating colorectal cancer remain unclear and warrant further investigation.

Four-dimensional Visual Analysis and Design Optimization of LC Filters at DC Side of Single-phase Diode Rectifiers

整流滤波电路用途广泛但其优化设计不易得到全局最优解。对单相桥式不控整流电路的LC滤波器进行深分析，得到输出平均电压、浪涌电流、振荡电压、谐波衰减比和体积等的表达式f（L，C,R），并在Matlab环境下用四维数据场展现其全局的值域分布，按需用不同交集来表征所须兼顾的多个设计目标，逐步导入约束条件来进行优化。实验结果表明，在滤波器外特性基本相同的前提下，基于数据场可视化算法的优化设计达到了体积缩小1／4的效果。

Visualization for Explanation of Deep Learning-Based Defect Detection Model Using Class Activation Map

Recently,convolutional neural network(CNN)-based visual inspec-tion has been developed to detect defects on building surfaces automatically.The CNN model demonstrates remarkable accuracy in image data analysis;however,the predicted results have uncertainty in providing accurate informa-tion to users because of the“black box”problem in the deep learning model.Therefore,this study proposes a visual explanation method to overcome the uncertainty limitation of CNN-based defect identification.The visual repre-sentative gradient-weights class activation mapping(Grad-CAM)method is adopted to provide visually explainable information.A visualizing evaluation index is proposed to quantitatively analyze visual representations;this index reflects a rough estimate of the concordance rate between the visualized heat map and intended defects.In addition,an ablation study,adopting three-branch combinations with the VGG16,is implemented to identify perfor-mance variations by visualizing predicted results.Experiments reveal that the proposed model,combined with hybrid pooling,batch normalization,and multi-attention modules,achieves the best performance with an accuracy of 97.77%,corresponding to an improvement of 2.49%compared with the baseline model.Consequently,this study demonstrates that reliable results from an automatic defect classification model can be provided to an inspector through the visual representation of the predicted results using CNN models.

An Interpretable CNN for the Segmentation of the Left Ventricle in Cardiac MRI by Real-Time Visualization

The interpretability of deep learning models has emerged as a compelling area in artificial intelligence research.The safety criteria for medical imaging are highly stringent,and models are required for an explanation.However,existing convolutional neural network solutions for left ventricular segmentation are viewed in terms of inputs and outputs.Thus,the interpretability of CNNs has come into the spotlight.Since medical imaging data are limited,many methods to fine-tune medical imaging models that are popular in transfer models have been built using massive public Image Net datasets by the transfer learning method.Unfortunately,this generates many unreliable parameters and makes it difficult to generate plausible explanations from these models.In this study,we trained from scratch rather than relying on transfer learning,creating a novel interpretable approach for autonomously segmenting the left ventricle with a cardiac MRI.Our enhanced GPU training system implemented interpretable global average pooling for graphics using deep learning.The deep learning tasks were simplified.Simplification included data management,neural network architecture,and training.Our system monitored and analyzed the gradient changes of different layers with dynamic visualizations in real-time and selected the optimal deployment model.Our results demonstrated that the proposed method was feasible and efficient:the Dice coefficient reached 94.48%,and the accuracy reached 99.7%.It was found that no current transfer learning models could perform comparably to the ImageNet transfer learning architectures.This model is lightweight and more convenient to deploy on mobile devices than transfer learning models.

Heterogeneous Image Knowledge Driven Visual Perception

Dear Editor,This letter is concerned with visual perception closely related to heterogeneous images.Facing the huge challenge brought by different image modalities,we propose a visual perception framework based on heterogeneous image knowledge,i.e.,the domain knowledge associated with specific vision tasks,to better address the corresponding visual perception problems.

集成PHAST-Visual Studio的岩溶区燃气管道灾害后果定量分析及应用

为科学评估岩溶区燃气管道灾害的后果影响程度,基于管道失效特征确定喷射火和蒸气云爆炸两种典型后果模式,研判适用于岩溶区燃气管道灾害的热辐射和冲击波超压危害准则,从危害面积、伤亡人数、经济损失、环境破坏4个维度提出岩溶区燃气管道灾害后果严重程度的评估模型体系,并结合Visual Studio平台开发“岩溶区燃气管道灾害后果分析软件”。立足岩溶区实际工程案例,结合区域经济社会发展、岩溶自然地质以及燃气管道工程特征,基于PHAST软件仿真分析灾害后果的影响范围,结合危害准则对区内人员、物体提出针对性灾害风险管控措施,并通过引入政府、行业、企业等颁布的标准条例,量化得出灾害后果的影响程度。结果表明:提出的PHAST-Visual Studio集成方法能够弥补以往研究的评估主观性问题,将社会科学思想带入工程风险评价研究,并通过计算机软件编程提高灾害后果分析效率,从而有助于显著控制岩溶区燃气管道灾害后果水平。

Filter and Embedded Feature Selection Methods to Meet Big Data Visualization Challenges

This study focuses on meeting the challenges of big data visualization by using of data reduction methods based the feature selection methods.To reduce the volume of big data and minimize model training time(Tt)while maintaining data quality.We contributed to meeting the challenges of big data visualization using the embedded method based“Select from model(SFM)”method by using“Random forest Importance algorithm(RFI)”and comparing it with the filter method by using“Select percentile(SP)”method based chi square“Chi2”tool for selecting the most important features,which are then fed into a classification process using the logistic regression(LR)algorithm and the k-nearest neighbor(KNN)algorithm.Thus,the classification accuracy(AC)performance of LRis also compared to theKNN approach in python on eight data sets to see which method produces the best rating when feature selection methods are applied.Consequently,the study concluded that the feature selection methods have a significant impact on the analysis and visualization of the data after removing the repetitive data and the data that do not affect the goal.After making several comparisons,the study suggests(SFMLR)using SFM based on RFI algorithm for feature selection,with LR algorithm for data classify.The proposal proved its efficacy by comparing its results with recent literature.

Visualization and early warning analysis of damage degree of surrounding rock mass in underground powerhouse

Based on the underground powerhouse of Shuangjiangkou hydropower station,Octree theory is adopted to define the indices of the microseismic(MS)spatial aggregation degree and the deviation values of MS count and energy.The relationship between the MS multiple parameters and surrounding rock mass instability is established from three aspects:time,space,and strength.Supplemented by the center frequency of the signal evolution characteristics,A fuzzy comprehensive evaluation model and the evolution trend of the MS event center frequency are constructed to quantitatively describe the early warning state of the surrounding rock mass instability.The results show that the multilevel tree structure and voxels generated based on the Octree theory fit relatively well with the set of MS points in threedimensional space.The fuzzy comprehensive evaluation model based on MS spatial aggregation and MS count and energy deviation values enables three-dimensional visualization of the potential damage area and damage extent of the surrounding rock mass.The warning time and potential damage zone quantified are highly consistent with the characteristics of MS precursors,with wide recognition and field investigation results,which fully validate the rationality and applicability of the proposed method.These findings can provide references for the early warning of surrounding rock mass instability in similar underground engineering.

Visualization of Landscape Changes in a 3D Environment Using the Storytelling Approach—The Example of the City of Pristina

This study proposes a detailed concept of how landscape changes can be transferred and communicated in a 3D environment using the storytelling approach. In 2018, Mocnik and Fairbairn argued that maps are good for representing a geographic space but texts have a better benefit than maps for telling a story [1]. A framework is presented on how a landscape change can be retrieved out of textual descriptions. A prototype of a 3D model with a projection on top of it was developed. The case study tells the story of the landscape change in the city of Pristina. The key element of the visualization is a timeline. Several media like cadastral maps, orthophotos, texts, graphics, and background sound are used and combined in an animated light show and the visualization was evaluated within a user study.

Visualization of Vector Tiles on CesiumJS Virtual Globe

Essentially, CesiumJS—which can be accessed through the link, http://cesiumjs.org, is an open-source JavaScript library for creating virtual globe environment in performance effective, high quality of rendering, precision, and user friendly. It is a wonderful tool for 3D-themed visualizations of earth. CesiumJS has a number of data sources, but none of them supports vector tile format. This article explains how to visualize Mapbox vector tiles in a CesiumJS virtual globe environment. CartoDB/BigQuery hosts vector tiles, and a process for producing vector tiles from massive vector data using the BigQuery tiler of CartoDB has been provided.