Background:In recent years,the development of digital imaging technology has had a significant influence in liver surgery.The ability to obtain a 3-dimensional(3D)visualization of the liver anatomy has provided surger...Background:In recent years,the development of digital imaging technology has had a significant influence in liver surgery.The ability to obtain a 3-dimensional(3D)visualization of the liver anatomy has provided surgery with virtual reality of simulation 3D computer models,3D printing models and more recently holograms and augmented reality(when virtual reality knowledge is superimposed onto reality).In addition,the utilization of real-time fluorescent imaging techniques based on indocyanine green(ICG)uptake allows clinicians to precisely delineate the liver anatomy and/or tumors within the parenchyma,applying the knowledge obtained preoperatively through digital imaging.The combination of both has transformed the abstract thinking until now based on 2D imaging into a 3D preoperative conception(virtual reality),enhanced with real-time visualization of the fluorescent liver structures,effectively facilitating intraoperative navigated liver surgery(augmented reality).Data sources:A literature search was performed from inception until January 2021 in MEDLINE(Pub Med),Embase,Cochrane library and database for systematic reviews(CDSR),Google Scholar,and National Institute for Health and Clinical Excellence(NICE)databases.Results:Fifty-one pertinent articles were retrieved and included.The different types of digital imaging technologies and the real-time navigated liver surgery were estimated and compared.Conclusions:ICG fluorescent imaging techniques can contribute essentially to the real-time definition of liver segments;as a result,precise hepatic resection can be guided by the presence of fluorescence.Furthermore,3D models can help essentially to further advancing of precision in hepatic surgery by permitting estimation of liver volume and functional liver remnant,delineation of resection lines along the liver segments and evaluation of tumor margins.In liver transplantation and especially in living donor liver transplantation(LDLT),3D printed models of the donor’s liver and models of the recipient’s hilar anatomy can contribute further to improving the results.In particular,pediatric LDLT abdominal cavity models can help to manage the largest challenge of this procedure,namely large-for-size syndrome.展开更多
AIM:To compare the short-term effectiveness of intelligent navigated laser photocoagulation and 577-nm subthreshold micropulse laser(SML)treatment in patients with chronic central serous chorioretinopathy(cCSC).METHOD...AIM:To compare the short-term effectiveness of intelligent navigated laser photocoagulation and 577-nm subthreshold micropulse laser(SML)treatment in patients with chronic central serous chorioretinopathy(cCSC).METHODS:This observational retrospective cohort study included 60 consecutive patients who underwent intelligent navigated laser photocoagulation(n=30)or 577-nm SML treatment(n=30)for cCSC between Jan.2021 and Oct.2022.During 3mo follow-up,all patients underwent assessments of best correct visual acuity(BCVA)and optical coherence tomography(OCT).RESULTS:The operation of laser treatment was successful in all cases.At 1mo,BCVA improved significantly more in the intelligent navigated laser photocoagulation group compared to the SML group(P<0.05).The change was not significantly different at 3mo(P>0.05).Central macular thickness(CMT)in the intelligent navigated laser photocoagulation group was lower than in the SML group at 1mo(P<0.05).The subfoveal choroidal thickness(SFCT)in two groups were all significantly improved at 3mo(all P<0.05).The change between two groups was not significantly different at 1mo or at 3mo(P>0.05).CONCLUSION:Intelligent navigated laser photocoagulation is superior to SML for treating cCSC,leading to better improvements in vision and CMT for short term.展开更多
Title: Analysis of factors influencing true blood loss in navigated total knee replacements. Objectives: To evaluate true blood loss in total knee replacements and analyze the various factors such as gender, BMI, diag...Title: Analysis of factors influencing true blood loss in navigated total knee replacements. Objectives: To evaluate true blood loss in total knee replacements and analyze the various factors such as gender, BMI, diagnosis, size of implants, duration of surgery, tourniquet usage etc. on calculated blood loss using formula by Nadler et al. All the cases included have been done using navigation system and no comparison with conventional jig based surgeries has been attempted. Methods: Retrospectively data of primary cemented total knee replacements performed from October 2012 to August 2013 were evaluated. All surgeries were performed using navigation system. The data collected included patient sex, height, weight and preoperative haemoglobin and hematocrit. The patients’ postoperative data of haemoglobin, hematocrit and drains were collected. All patients had their CBC done on 2nd post operative day. Any data on transfusions that patients received were also collected. We also collected data regarding the size of implant used. We calculated true blood based on formula given by Nadler, Hidalgo & Bloch. We excluded patients whose data were incomplete or who received tranexamic acid. Patients who needed stems (femoral or tibial) were also excluded from this study. Results: The average true calculated blood loss was 959.44 ml. BMI did not have any effect on blood loss. But larger size implants were associated with more blood loss. Conclusion: The preoperative haemoglobin is one of the most important factors in determining transfusion following the knee replacement. Male gender and larger implants are associated with more blood loss. BMI, diagnosis of OA or RA, tourniquet usage and time have no significant effect on blood loss. Our calculated blood loss compares favourably with published literature.展开更多
Augmented-and mixed-reality technologies have pioneered the realization of real-time fusion and interactive projection for laparoscopic surgeries.Indocyanine green fluorescence imaging technology has enabled anatomica...Augmented-and mixed-reality technologies have pioneered the realization of real-time fusion and interactive projection for laparoscopic surgeries.Indocyanine green fluorescence imaging technology has enabled anatomical,functional,and radical hepatectomy through tumor identification and localization of target hepatic segments,driving a transformative shift in themanagement of hepatic surgical diseases,moving away from traditional,empirical diagnostic and treatment approaches toward digital,intelligent ones.The Hepatic Surgery Group of the Surgery Branch of the Chinese Medical Association,Digital Medicine Branch of the Chinese Medical Association,Digital Intelligent Surgery Committee of the Chinese Society of ResearchHospitals,and Liver Cancer Committee of the Chinese Medical Doctor Association organized the relevant experts in China to formulate this consensus.This consensus provides a comprehensive outline of the principles,advantages,processes,and key considerations associated with the application of augmented reality and mixed-reality technology combined with indocyanine green fluorescence imaging technology for hepatic segmental and subsegmental resection.The purpose is to streamline and standardize the application of these technologies.展开更多
The brain is a complex organ that requires precise mapping to understand its structure and function.Brain atlases provide a powerful tool for studying brain circuits,discovering biological markers for early diagnosis,...The brain is a complex organ that requires precise mapping to understand its structure and function.Brain atlases provide a powerful tool for studying brain circuits,discovering biological markers for early diagnosis,and developing personalized treatments for neuropsychiatric disorders.Neuromodulation techniques,such as transcranial magnetic stimulation and deep brain stimulation,have revolutionized clinical therapies for neuropsychiatric disorders.However,the lack of fine-scale brain atlases limits the precision and effectiveness of these techniques.Advances in neuroimaging and machine learning techniques have led to the emergence of stereotactic-assisted neurosurgery and navigation systems.Still,the individual variability among patients and the diversity of brain diseases make it necessary to develop personalized solutions.The article provides an overview of recent advances in individualized brain mapping and navigated neuromodulation and discusses the methodological profiles,advantages,disadvantages,and future trends of these techniques.The article concludes by posing open questions about the future development of individualized brain mapping and navigated neuromodulation.展开更多
Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT^(*)),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narr...Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT^(*)),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narrow passages,slow convergence,and high computational costs.To address these challenges,this paper proposes a novel hybrid global path planning algorithm integrating Gaussian sampling and quadtree optimization(RRT^(*)-GSQ).This methodology aims to enhance path planning by synergistically combining a Gaussian mixture sampling strategy to improve node generation in critical regions,an adaptive step-size and direction optimization mechanism for enhanced obstacle avoidance,a Quadtree-AABB collision detection framework to lower computational complexity,and a dynamic iteration control strategy for more efficient convergence.In obstacle-free and obstructed scenarios,compared with the conventional RRT^(*),the proposed algorithm reduced the number of node evaluations by 67.57%and 62.72%,and decreased the search time by 79.72%and 78.52%,respectively.In path tracking tests,the proposed algorithm achieved substantial reductions in RMSE of the final path compared to the conventional RRT^(*).Specifically,the lateral RMSE was reduced by 41.5%in obstacle-free environments and 59.3%in obstructed environments,while the longitudinal RMSE was reduced by 57.2%and 58.5%,respectively.Furthermore,the maximum absolute errors in both lateral and longitudinal directions were constrained within 0.75 m.Field validation experiments in an operational orchard confirmed the algorithm's practical effectiveness,showing reductions in the mean tracking error of 47.6%(obstacle-free)and 58.3%(with obstructed),alongside a 5.1%and 7.2%shortening of the path length compared to the baseline method.The proposed algorithm effectively enhances path planning efficiency and navigation accuracy for robots,presenting a superior solution for high-precision autonomous navigation of agricultural robots in orchard environments and holding significant value for engineering applications.展开更多
Unmanned aerial vehicles(UAVs),especially quadcopters,have become indispensable in numerous industrial and scientific applications due to their flexibility,lowcost,and capability to operate in dynamic environments.Thi...Unmanned aerial vehicles(UAVs),especially quadcopters,have become indispensable in numerous industrial and scientific applications due to their flexibility,lowcost,and capability to operate in dynamic environments.This paper presents a complete design and implementation of a compact autonomous quadcopter capable of trajectory tracking,object detection,precision landing,and real-time telemetry via long-range communication protocols.The system integrates an onboard flight controller running real-time sensor fusion algorithms,a vision-based detection system on a companion single-board computer,and a telemetry unit using Long Range(LoRa)communication.Extensive flight tests were conducted to validate the system’s stability,communication range,and autonomous capabilities.Potential applications in law enforcement,agriculture,search and rescue,and environmental monitoring are also discussed.展开更多
The satellite-based augmentation system(SBAS)provides differential and integrity augmentation services for life safety fields of aviation and navigation.However,the signal structure of SBAS is public,which incurs a ri...The satellite-based augmentation system(SBAS)provides differential and integrity augmentation services for life safety fields of aviation and navigation.However,the signal structure of SBAS is public,which incurs a risk of spoofing attacks.To improve the anti-spoofing capability of the SBAS,European Union and the United States conduct research on navigation message authentication,and promote the standardization of SBAS message authentication.For the development of Beidou satellite-based augmentation system(BDSBAS),this paper proposes navigation message authentication based on the Chinese commercial cryptographic standards.Firstly,this paper expounds the architecture and principles of the SBAS message authentication,and then carries out the design of timed efficient streaming losstolerant authentication scheme(TESLA)and elliptic curve digital signature algorithm(ECDSA)authentication schemes based on Chinese commercial cryptographic standards,message arrangement and the design of over-the-air rekeying(OTAR)message.Finally,this paper conducts a theoretical analysis of the time between authentications(TBA)and maximum authentication latency(MAL)for L5 TESLA-I and L5 ECDSA-Q,and further simulates the reception time of OTAR message,TBA and MAL from the aspects of OTAR message weight and demodulation error rate.The simulation results can provide theoretical supports for the standardization of BDSBAS message authentication.展开更多
Objectives:One of the most notable challenges in endoscopic procedures is maintaining correct orientation.Mental rotation exercise(MRE)has been suggested as a potential aid for improving orientation.However,there is a...Objectives:One of the most notable challenges in endoscopic procedures is maintaining correct orientation.Mental rotation exercise(MRE)has been suggested as a potential aid for improving orientation.However,there is a lack of research on designing MREs with varying difficultylevels for training purposes.Furthermore,few studies provide solid evidence linking MRE difficultylevels with cognitive load measurements.This study aims to address this gap by investigating the correlation between the MRE difficultylevels and participants’cognitive load,as measured by pupil dilation.Method:We recruited 33 participants to perform MREs on a computer equipped with a screen-mounted eye-tracker.The test consisted of 15 MREs,with the first10 relatively easy(traditional cube)and the next 5 more complex(invented molecule).The participants’eye movements during MREs were recorded.The participants’MRE scores and pupil dilation were obtained and compared between two MRE difficultylevels.Results:The participants who performed traditional cube MREs achieved significantlybetter MRE scores(0.77±0.11 vs.0.58±0.03,p<0.001)and lower pupil dilation(0.27±0.04 pixels vs.0.47±0.09 pixels,p<0.001)than did those who performed the invented molecule MREs.Moreover,there were significant negative correlations(r=0.62,p=0.015)between pupil dilation and MRE scores.Conclusions:The results revealed a significantnegative correlation between MRE scores and pupil dilation.The more challenging MRE questions led to worse MRE scores but increased pupil dilation.The MRE difficultylevels can be evaluated not only by the degrees or dimensions with which the objects were rotated but also by the participants’MRE scores and pupil dilation.The results of this study provide a basis for training orientation skills in endoscopy using MREs.By incorporating MREs with varying difficultylevels,customized training programs can be developed to enhance camera navigation in endoscopic and laparoscopic procedures.展开更多
Surgical navigation has evolved significantly through advances in augmented reality,virtual reality,and mixed reality,improving precision and safety across many clinical applications,including neurosurgery,maxillofaci...Surgical navigation has evolved significantly through advances in augmented reality,virtual reality,and mixed reality,improving precision and safety across many clinical applications,including neurosurgery,maxillofacial,spinal,and arthroplasty procedures.By integrating preoperative imaging with real-time intraoperative data,these systems provide dynamic guidance,reduce radiation exposure,and minimize tissue damage.Key challenges persist,including intraoperative registration accuracy,flexible tissue deformation,respiratory compensation,and real-time imaging quality.Emerging solutions include artificial intelligence-driven segmentation,deformation-field modeling,and hybrid registration techniques.Future developments will include lightweight,portable systems,improved non-rigid registration algorithms,and greater clinical adoption.Despite advances in rigid-tissue applications,soft-tissue navigation requires additional innovation to address motion variability and registration reliability,ultimately advancing minimally invasive surgery and precision medicine.展开更多
Background:Artificial intelligence(AI)-assisted threedimensional(3D)surgical platforms,integrated with augmented reality,have the potential to improve intraoperative anatomical recognition and provide surgeons with an...Background:Artificial intelligence(AI)-assisted threedimensional(3D)surgical platforms,integrated with augmented reality,have the potential to improve intraoperative anatomical recognition and provide surgeons with an immersive,dynamic operating environment during urooncological procedures.This review aims to examine the current applications of AI in robotic uro-oncology,with a particular focus on its role in facilitating intraoperative navigation during complex surgeries.Methods:A systematic literature search was performed across PubMed,the National Library of Medicine,MEDLINE,the Cochrane Central Register of Controlled Trials(CENTRAL),ClinicalTrials.gov,and Google Scholar to identify relevant studies published up to July 2025.The search strategy incorporated a predefined set of keywords,including AI,machine learning,radical prostatectomy(RP),robotic-assisted radical prostatectomy(RARP),robotassisted partial nephrectomy(RAPN),and robot-assisted radical cystectomy(RARC).Only clinical trials,full-text peer-reviewed publications,and original research articles were included.Studies were eligible for inclusion if they evaluated or described applications of AI in RARP,RAPN,or RARC.Results:Technological advancements have substantially transformed the field of uro-oncologic surgery.In particular,AI and AI-assisted intraoperative navigation in RARP demonstrate considerable potential to objectively assess surgical performance and predict clinical outcomes.In RAPN,the adoption of preoperative,interactive 3D virtualmodels for surgical planning has influenced surgical decisions,thus,enhanced precision in resection planning correlates with superior nephron-sparing outcomes and optimized selective clamping.AI applications in RARC,techniques such as augmented reality(AR)can overlay critical information on the surgical field,by facilitating navigation through complex anatomical planes and enhancing identification of critical structures.Conclusion:AI appears to enhance robotic uro-oncologic procedures by increasing operative precision and supporting individualised surgical treatment strategies.展开更多
Autonomous navigation is a key technology for unmanned motion platforms to perform their tasks smoothly.The current approaches for daytime polarization navigation have been extensively researched.However,the polarizat...Autonomous navigation is a key technology for unmanned motion platforms to perform their tasks smoothly.The current approaches for daytime polarization navigation have been extensively researched.However,the polarization light intensity is the fundamental information within the polarization image,and the light intensity at night is 6-8 orders of magnitude lower than that during the day,which increase the noise and the loss of local polarization information due to occlusion,resulting in a significant decrease in the polarization orientation accuracy.Aimed at the problem,a bio-inspired model is introduced to denoise and enhance weak nighttime polarization patterns.Further,to address the issue of outlier interference in the occluded environment during practical application,a fast-fitting method of the solar meridian based on the anti-symmetric distribution of the polarization angle adjusted by Proportional and Differential(PD)control is proposed.The experimental results show that the method proposed in this paper achieves a dynamic orientation error Root Mean Square Error(RMSE)of 0.7°in the weak polarization mode at night and in the presence of local occlusion.The proposed method has strong robustness under weak polarization occlusion at night,and the orientation accuracy is improved by 97%and 80%in comparison to the least squares method,which provides a new method for polarization navigation at night.This effectively improves the robustness and environmental applicability of the bionic polarization compass for nighttime applications.展开更多
Microelectromechanical systems(MEMS)technology has gained significant attention over the past decade for measuring inertial angular velocity.However,due to inherent complexity,MEMS gyroscopes typically feature up to t...Microelectromechanical systems(MEMS)technology has gained significant attention over the past decade for measuring inertial angular velocity.However,due to inherent complexity,MEMS gyroscopes typically feature up to ten times more parameters than traditional sensors,making selection a challenging task even for experts.This study addresses this challenge,focusing on defensive guidance,navigation,and control(GNC)systems where precise and reliable angular velocity measurement is critical to overall performance.A comprehensive mathematical model is introduced to encapsulate all key MEMS parameters,accompanied by discussions on calibration and Allan variance interpretation.For six leading MEMS gyroscope applications,namely inertial navigation,integrated navigation,autopilot systems,rotating projectiles,homing guidance,and north finding,the most critical parameters are identified,distinguishing suitable and unsuitable sensor choices.Special emphasis is placed on inertial navigation systems,where practical rules of thumb for error evaluation are derived using six degrees of freedom motion equations.Rigorous simulations demonstrate the influence of various sensor parameters through real-world case studies,including static navigation,multi-rotor attitude estimation,gimbal stabilization,and north finding via a turntable.This work aims to be a beacon for practitioners across diverse fields,empowering them to make more informed design decisions.展开更多
The current inertial measurement unit(IMU)and odometry fusion navigation algorithms often incorporate non-holonomic constraints(NHC)to obtain three-dimensional velocity in the navigation frame.However,due to the integ...The current inertial measurement unit(IMU)and odometry fusion navigation algorithms often incorporate non-holonomic constraints(NHC)to obtain three-dimensional velocity in the navigation frame.However,due to the integral nature of the dead reckoning algorithm,the attitude errors of the IMU accumulate over time,causing the velocity transformation results to fail to accurately reflect the threedimensional velocity in the navigation frame.Based on the fact that during a vehicle's horizontal and uniform motion,the vertical acceleration is consistent with gravitational acceleration,this paper proposes an IMU/odometry fusion navigation algorithm based on horizontal attitude constraints(HAC).Building on non-holonomic constraints,this algorithm determines the motion state of the vehicle through accelerometer output and zeroes out the pitch and roll angles during horizontal and uniform motion.Verified through two sets of real-world vehicle test data,this algorithm improves horizontal positioning accuracy by approximately 63%and 70%,and vertical positioning accuracy by 98%and 97%,compared with the traditional NHC IMU/odometer fusion algorithm.展开更多
With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Lap...With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Laparoscopic-endoscopic cooperative surgery combined with sentinel lymph node navigation surgery(LECSSNNS)has drawn increasing interest because of its dual benefits of minimal invasiveness and organ function preservation.However,robust evidence-based support for guiding clinical implementation remains limited.To address this gap,we systematically evaluated available studies on the clinical application of LECS-SNNS in EGC and integrated expert insights to formulate 20 recommendations.These included preoperative assessment,surgical techniques,intraoperative endoscopic procedures,pathological evaluation,postoperative care,and follow-up.This consensus aimed to provide comprehensive guidance for the standardized application of LECS-SNNS,thereby advancing precise,minimally invasive,and function-preserving treatment for EGC.展开更多
The selection of a suitable navigation area is pivotal in aircraft scene matching guidance technology.This study addresses the challenge of identifying suitable reference image ranges for precise scene matching,which ...The selection of a suitable navigation area is pivotal in aircraft scene matching guidance technology.This study addresses the challenge of identifying suitable reference image ranges for precise scene matching,which is crucial for enhancing aircraft positioning accuracy.Traditional methods for image matchability analysis are often limited by their reliance on manual feature parameter design and threshold-based filtering,resulting in suboptimal accuracy and efficiency.This paper proposes a novel network architecture for selecting suitable navigation areas using image Matching Level Segmentation(MLSNet).The approach involves two key innovations:a method for generating segmentation labels that quantify matchability levels and an end-to-end network architecture for rapid and precise prediction of reference image matchability segmentation maps.The network includes two core modules:the saliency analysis module uses multi-layer convolutional networks to accurately detect image saliency features across various levels and scales;the multidimensional attention module utilizes attention mechanisms to focus on feature channels and spatial neighborhood scenes to assess the image’s matchability.Our method was rigorously tested on an extensive collection of remote sensing images,where it was benchmarked against a range of both traditional and cutting-edge deep learning methods.The findings indicate that MLSNet is significantly superior to traditional methods in accuracy and efficiency of matchability analysis,and is also relatively ahead of state-of-the-art deep learning models.展开更多
文摘Background:In recent years,the development of digital imaging technology has had a significant influence in liver surgery.The ability to obtain a 3-dimensional(3D)visualization of the liver anatomy has provided surgery with virtual reality of simulation 3D computer models,3D printing models and more recently holograms and augmented reality(when virtual reality knowledge is superimposed onto reality).In addition,the utilization of real-time fluorescent imaging techniques based on indocyanine green(ICG)uptake allows clinicians to precisely delineate the liver anatomy and/or tumors within the parenchyma,applying the knowledge obtained preoperatively through digital imaging.The combination of both has transformed the abstract thinking until now based on 2D imaging into a 3D preoperative conception(virtual reality),enhanced with real-time visualization of the fluorescent liver structures,effectively facilitating intraoperative navigated liver surgery(augmented reality).Data sources:A literature search was performed from inception until January 2021 in MEDLINE(Pub Med),Embase,Cochrane library and database for systematic reviews(CDSR),Google Scholar,and National Institute for Health and Clinical Excellence(NICE)databases.Results:Fifty-one pertinent articles were retrieved and included.The different types of digital imaging technologies and the real-time navigated liver surgery were estimated and compared.Conclusions:ICG fluorescent imaging techniques can contribute essentially to the real-time definition of liver segments;as a result,precise hepatic resection can be guided by the presence of fluorescence.Furthermore,3D models can help essentially to further advancing of precision in hepatic surgery by permitting estimation of liver volume and functional liver remnant,delineation of resection lines along the liver segments and evaluation of tumor margins.In liver transplantation and especially in living donor liver transplantation(LDLT),3D printed models of the donor’s liver and models of the recipient’s hilar anatomy can contribute further to improving the results.In particular,pediatric LDLT abdominal cavity models can help to manage the largest challenge of this procedure,namely large-for-size syndrome.
文摘AIM:To compare the short-term effectiveness of intelligent navigated laser photocoagulation and 577-nm subthreshold micropulse laser(SML)treatment in patients with chronic central serous chorioretinopathy(cCSC).METHODS:This observational retrospective cohort study included 60 consecutive patients who underwent intelligent navigated laser photocoagulation(n=30)or 577-nm SML treatment(n=30)for cCSC between Jan.2021 and Oct.2022.During 3mo follow-up,all patients underwent assessments of best correct visual acuity(BCVA)and optical coherence tomography(OCT).RESULTS:The operation of laser treatment was successful in all cases.At 1mo,BCVA improved significantly more in the intelligent navigated laser photocoagulation group compared to the SML group(P<0.05).The change was not significantly different at 3mo(P>0.05).Central macular thickness(CMT)in the intelligent navigated laser photocoagulation group was lower than in the SML group at 1mo(P<0.05).The subfoveal choroidal thickness(SFCT)in two groups were all significantly improved at 3mo(all P<0.05).The change between two groups was not significantly different at 1mo or at 3mo(P>0.05).CONCLUSION:Intelligent navigated laser photocoagulation is superior to SML for treating cCSC,leading to better improvements in vision and CMT for short term.
文摘Title: Analysis of factors influencing true blood loss in navigated total knee replacements. Objectives: To evaluate true blood loss in total knee replacements and analyze the various factors such as gender, BMI, diagnosis, size of implants, duration of surgery, tourniquet usage etc. on calculated blood loss using formula by Nadler et al. All the cases included have been done using navigation system and no comparison with conventional jig based surgeries has been attempted. Methods: Retrospectively data of primary cemented total knee replacements performed from October 2012 to August 2013 were evaluated. All surgeries were performed using navigation system. The data collected included patient sex, height, weight and preoperative haemoglobin and hematocrit. The patients’ postoperative data of haemoglobin, hematocrit and drains were collected. All patients had their CBC done on 2nd post operative day. Any data on transfusions that patients received were also collected. We also collected data regarding the size of implant used. We calculated true blood based on formula given by Nadler, Hidalgo & Bloch. We excluded patients whose data were incomplete or who received tranexamic acid. Patients who needed stems (femoral or tibial) were also excluded from this study. Results: The average true calculated blood loss was 959.44 ml. BMI did not have any effect on blood loss. But larger size implants were associated with more blood loss. Conclusion: The preoperative haemoglobin is one of the most important factors in determining transfusion following the knee replacement. Male gender and larger implants are associated with more blood loss. BMI, diagnosis of OA or RA, tourniquet usage and time have no significant effect on blood loss. Our calculated blood loss compares favourably with published literature.
基金National Key Research and Development Program(2016YFC0106500800)NationalMajor Scientific Instruments and Equipments Development Project of National Natural Science Foundation of China(81627805)+3 种基金National Natural Science Foundation of China-Guangdong Joint Fund Key Program(U1401254)National Natural Science Foundation of China Mathematics Tianyuan Foundation(12026602)Guangdong Provincial Natural Science Foundation Team Project(6200171)Guangdong Provincial Health Appropriate Technology Promotion Project(20230319214525105,20230322152307666).
文摘Augmented-and mixed-reality technologies have pioneered the realization of real-time fusion and interactive projection for laparoscopic surgeries.Indocyanine green fluorescence imaging technology has enabled anatomical,functional,and radical hepatectomy through tumor identification and localization of target hepatic segments,driving a transformative shift in themanagement of hepatic surgical diseases,moving away from traditional,empirical diagnostic and treatment approaches toward digital,intelligent ones.The Hepatic Surgery Group of the Surgery Branch of the Chinese Medical Association,Digital Medicine Branch of the Chinese Medical Association,Digital Intelligent Surgery Committee of the Chinese Society of ResearchHospitals,and Liver Cancer Committee of the Chinese Medical Doctor Association organized the relevant experts in China to formulate this consensus.This consensus provides a comprehensive outline of the principles,advantages,processes,and key considerations associated with the application of augmented reality and mixed-reality technology combined with indocyanine green fluorescence imaging technology for hepatic segmental and subsegmental resection.The purpose is to streamline and standardize the application of these technologies.
基金partially supported by STI2030-Major Projects(No.2021ZD0200200)the Natural Science Foundation of China(Nos.82072099,91432302,31620103905,and 62250058)+1 种基金the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDB32030200)the National Key Research&Development Program of China(No.2017YFA0105203)
文摘The brain is a complex organ that requires precise mapping to understand its structure and function.Brain atlases provide a powerful tool for studying brain circuits,discovering biological markers for early diagnosis,and developing personalized treatments for neuropsychiatric disorders.Neuromodulation techniques,such as transcranial magnetic stimulation and deep brain stimulation,have revolutionized clinical therapies for neuropsychiatric disorders.However,the lack of fine-scale brain atlases limits the precision and effectiveness of these techniques.Advances in neuroimaging and machine learning techniques have led to the emergence of stereotactic-assisted neurosurgery and navigation systems.Still,the individual variability among patients and the diversity of brain diseases make it necessary to develop personalized solutions.The article provides an overview of recent advances in individualized brain mapping and navigated neuromodulation and discusses the methodological profiles,advantages,disadvantages,and future trends of these techniques.The article concludes by posing open questions about the future development of individualized brain mapping and navigated neuromodulation.
基金National Natural Science Foundation of China(32301712)Natural Science Foundation of Jiangsu Province(BK20230548,BK20250876)+2 种基金Project of Faculty of Agricultural Equipment of Jiangsu University(NGXB20240203)A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD-2023-87)Open Funding Project of the Key Laboratory of Modern Agricultural Equipment and Technology(Jiangsu University),Ministry of Education(MAET202101)。
文摘Traditional sampling-based path planning algorithms,such as the rapidly-exploring random tree star(RRT^(*)),encounter critical limitations in unstructured orchard environments,including low sampling efficiency in narrow passages,slow convergence,and high computational costs.To address these challenges,this paper proposes a novel hybrid global path planning algorithm integrating Gaussian sampling and quadtree optimization(RRT^(*)-GSQ).This methodology aims to enhance path planning by synergistically combining a Gaussian mixture sampling strategy to improve node generation in critical regions,an adaptive step-size and direction optimization mechanism for enhanced obstacle avoidance,a Quadtree-AABB collision detection framework to lower computational complexity,and a dynamic iteration control strategy for more efficient convergence.In obstacle-free and obstructed scenarios,compared with the conventional RRT^(*),the proposed algorithm reduced the number of node evaluations by 67.57%and 62.72%,and decreased the search time by 79.72%and 78.52%,respectively.In path tracking tests,the proposed algorithm achieved substantial reductions in RMSE of the final path compared to the conventional RRT^(*).Specifically,the lateral RMSE was reduced by 41.5%in obstacle-free environments and 59.3%in obstructed environments,while the longitudinal RMSE was reduced by 57.2%and 58.5%,respectively.Furthermore,the maximum absolute errors in both lateral and longitudinal directions were constrained within 0.75 m.Field validation experiments in an operational orchard confirmed the algorithm's practical effectiveness,showing reductions in the mean tracking error of 47.6%(obstacle-free)and 58.3%(with obstructed),alongside a 5.1%and 7.2%shortening of the path length compared to the baseline method.The proposed algorithm effectively enhances path planning efficiency and navigation accuracy for robots,presenting a superior solution for high-precision autonomous navigation of agricultural robots in orchard environments and holding significant value for engineering applications.
文摘Unmanned aerial vehicles(UAVs),especially quadcopters,have become indispensable in numerous industrial and scientific applications due to their flexibility,lowcost,and capability to operate in dynamic environments.This paper presents a complete design and implementation of a compact autonomous quadcopter capable of trajectory tracking,object detection,precision landing,and real-time telemetry via long-range communication protocols.The system integrates an onboard flight controller running real-time sensor fusion algorithms,a vision-based detection system on a companion single-board computer,and a telemetry unit using Long Range(LoRa)communication.Extensive flight tests were conducted to validate the system’s stability,communication range,and autonomous capabilities.Potential applications in law enforcement,agriculture,search and rescue,and environmental monitoring are also discussed.
基金supported by National Natural Science Foundation of China:Space-based occultation detection with ground-based GNSS atmospheric horizontal gradient model(41904033).
文摘The satellite-based augmentation system(SBAS)provides differential and integrity augmentation services for life safety fields of aviation and navigation.However,the signal structure of SBAS is public,which incurs a risk of spoofing attacks.To improve the anti-spoofing capability of the SBAS,European Union and the United States conduct research on navigation message authentication,and promote the standardization of SBAS message authentication.For the development of Beidou satellite-based augmentation system(BDSBAS),this paper proposes navigation message authentication based on the Chinese commercial cryptographic standards.Firstly,this paper expounds the architecture and principles of the SBAS message authentication,and then carries out the design of timed efficient streaming losstolerant authentication scheme(TESLA)and elliptic curve digital signature algorithm(ECDSA)authentication schemes based on Chinese commercial cryptographic standards,message arrangement and the design of over-the-air rekeying(OTAR)message.Finally,this paper conducts a theoretical analysis of the time between authentications(TBA)and maximum authentication latency(MAL)for L5 TESLA-I and L5 ECDSA-Q,and further simulates the reception time of OTAR message,TBA and MAL from the aspects of OTAR message weight and demodulation error rate.The simulation results can provide theoretical supports for the standardization of BDSBAS message authentication.
文摘Objectives:One of the most notable challenges in endoscopic procedures is maintaining correct orientation.Mental rotation exercise(MRE)has been suggested as a potential aid for improving orientation.However,there is a lack of research on designing MREs with varying difficultylevels for training purposes.Furthermore,few studies provide solid evidence linking MRE difficultylevels with cognitive load measurements.This study aims to address this gap by investigating the correlation between the MRE difficultylevels and participants’cognitive load,as measured by pupil dilation.Method:We recruited 33 participants to perform MREs on a computer equipped with a screen-mounted eye-tracker.The test consisted of 15 MREs,with the first10 relatively easy(traditional cube)and the next 5 more complex(invented molecule).The participants’eye movements during MREs were recorded.The participants’MRE scores and pupil dilation were obtained and compared between two MRE difficultylevels.Results:The participants who performed traditional cube MREs achieved significantlybetter MRE scores(0.77±0.11 vs.0.58±0.03,p<0.001)and lower pupil dilation(0.27±0.04 pixels vs.0.47±0.09 pixels,p<0.001)than did those who performed the invented molecule MREs.Moreover,there were significant negative correlations(r=0.62,p=0.015)between pupil dilation and MRE scores.Conclusions:The results revealed a significantnegative correlation between MRE scores and pupil dilation.The more challenging MRE questions led to worse MRE scores but increased pupil dilation.The MRE difficultylevels can be evaluated not only by the degrees or dimensions with which the objects were rotated but also by the participants’MRE scores and pupil dilation.The results of this study provide a basis for training orientation skills in endoscopy using MREs.By incorporating MREs with varying difficultylevels,customized training programs can be developed to enhance camera navigation in endoscopic and laparoscopic procedures.
基金Supported by the National Natural Science Foundation of China(NSFC)under Grants 62025104,62422102,62331005,62301034,and U22A2052the Beijing Natural Science Foundation-Daxing Innovation Joint Fund(L256040).
文摘Surgical navigation has evolved significantly through advances in augmented reality,virtual reality,and mixed reality,improving precision and safety across many clinical applications,including neurosurgery,maxillofacial,spinal,and arthroplasty procedures.By integrating preoperative imaging with real-time intraoperative data,these systems provide dynamic guidance,reduce radiation exposure,and minimize tissue damage.Key challenges persist,including intraoperative registration accuracy,flexible tissue deformation,respiratory compensation,and real-time imaging quality.Emerging solutions include artificial intelligence-driven segmentation,deformation-field modeling,and hybrid registration techniques.Future developments will include lightweight,portable systems,improved non-rigid registration algorithms,and greater clinical adoption.Despite advances in rigid-tissue applications,soft-tissue navigation requires additional innovation to address motion variability and registration reliability,ultimately advancing minimally invasive surgery and precision medicine.
文摘Background:Artificial intelligence(AI)-assisted threedimensional(3D)surgical platforms,integrated with augmented reality,have the potential to improve intraoperative anatomical recognition and provide surgeons with an immersive,dynamic operating environment during urooncological procedures.This review aims to examine the current applications of AI in robotic uro-oncology,with a particular focus on its role in facilitating intraoperative navigation during complex surgeries.Methods:A systematic literature search was performed across PubMed,the National Library of Medicine,MEDLINE,the Cochrane Central Register of Controlled Trials(CENTRAL),ClinicalTrials.gov,and Google Scholar to identify relevant studies published up to July 2025.The search strategy incorporated a predefined set of keywords,including AI,machine learning,radical prostatectomy(RP),robotic-assisted radical prostatectomy(RARP),robotassisted partial nephrectomy(RAPN),and robot-assisted radical cystectomy(RARC).Only clinical trials,full-text peer-reviewed publications,and original research articles were included.Studies were eligible for inclusion if they evaluated or described applications of AI in RARP,RAPN,or RARC.Results:Technological advancements have substantially transformed the field of uro-oncologic surgery.In particular,AI and AI-assisted intraoperative navigation in RARP demonstrate considerable potential to objectively assess surgical performance and predict clinical outcomes.In RAPN,the adoption of preoperative,interactive 3D virtualmodels for surgical planning has influenced surgical decisions,thus,enhanced precision in resection planning correlates with superior nephron-sparing outcomes and optimized selective clamping.AI applications in RARC,techniques such as augmented reality(AR)can overlay critical information on the surgical field,by facilitating navigation through complex anatomical planes and enhancing identification of critical structures.Conclusion:AI appears to enhance robotic uro-oncologic procedures by increasing operative precision and supporting individualised surgical treatment strategies.
基金co-supported by the Excellent Youth Foundation of Shanxi Province,China(No.202103021222011)the Key Research and Development project of Shanxi Province of China(No.202202020101002)+3 种基金the Fundamental Research Program of Shanxi Province of China(No.202303021211150)the Aviation Science Foundation of China(No.2022Z0220U0002)the Graduate Education Innovation Plan Project of Shanxi Province,China(No.2023KY588)the Shanxi Province Key Laboratory of Quantum Sensing and Precision Measurement,China(No.201905D121001).
文摘Autonomous navigation is a key technology for unmanned motion platforms to perform their tasks smoothly.The current approaches for daytime polarization navigation have been extensively researched.However,the polarization light intensity is the fundamental information within the polarization image,and the light intensity at night is 6-8 orders of magnitude lower than that during the day,which increase the noise and the loss of local polarization information due to occlusion,resulting in a significant decrease in the polarization orientation accuracy.Aimed at the problem,a bio-inspired model is introduced to denoise and enhance weak nighttime polarization patterns.Further,to address the issue of outlier interference in the occluded environment during practical application,a fast-fitting method of the solar meridian based on the anti-symmetric distribution of the polarization angle adjusted by Proportional and Differential(PD)control is proposed.The experimental results show that the method proposed in this paper achieves a dynamic orientation error Root Mean Square Error(RMSE)of 0.7°in the weak polarization mode at night and in the presence of local occlusion.The proposed method has strong robustness under weak polarization occlusion at night,and the orientation accuracy is improved by 97%and 80%in comparison to the least squares method,which provides a new method for polarization navigation at night.This effectively improves the robustness and environmental applicability of the bionic polarization compass for nighttime applications.
文摘Microelectromechanical systems(MEMS)technology has gained significant attention over the past decade for measuring inertial angular velocity.However,due to inherent complexity,MEMS gyroscopes typically feature up to ten times more parameters than traditional sensors,making selection a challenging task even for experts.This study addresses this challenge,focusing on defensive guidance,navigation,and control(GNC)systems where precise and reliable angular velocity measurement is critical to overall performance.A comprehensive mathematical model is introduced to encapsulate all key MEMS parameters,accompanied by discussions on calibration and Allan variance interpretation.For six leading MEMS gyroscope applications,namely inertial navigation,integrated navigation,autopilot systems,rotating projectiles,homing guidance,and north finding,the most critical parameters are identified,distinguishing suitable and unsuitable sensor choices.Special emphasis is placed on inertial navigation systems,where practical rules of thumb for error evaluation are derived using six degrees of freedom motion equations.Rigorous simulations demonstrate the influence of various sensor parameters through real-world case studies,including static navigation,multi-rotor attitude estimation,gimbal stabilization,and north finding via a turntable.This work aims to be a beacon for practitioners across diverse fields,empowering them to make more informed design decisions.
基金from the National Key Research and Development Program project"Adaptive Navigation Software and Hardware Technology(2018YFB0505200)."。
文摘The current inertial measurement unit(IMU)and odometry fusion navigation algorithms often incorporate non-holonomic constraints(NHC)to obtain three-dimensional velocity in the navigation frame.However,due to the integral nature of the dead reckoning algorithm,the attitude errors of the IMU accumulate over time,causing the velocity transformation results to fail to accurately reflect the threedimensional velocity in the navigation frame.Based on the fact that during a vehicle's horizontal and uniform motion,the vertical acceleration is consistent with gravitational acceleration,this paper proposes an IMU/odometry fusion navigation algorithm based on horizontal attitude constraints(HAC).Building on non-holonomic constraints,this algorithm determines the motion state of the vehicle through accelerometer output and zeroes out the pitch and roll angles during horizontal and uniform motion.Verified through two sets of real-world vehicle test data,this algorithm improves horizontal positioning accuracy by approximately 63%and 70%,and vertical positioning accuracy by 98%and 97%,compared with the traditional NHC IMU/odometer fusion algorithm.
基金supported by National Key Research and Development Program of China(No.2023YFC2507406)National Natural Science Foundation of China(No.82300646)+6 种基金Beijing Natural Science Foundation(No.7232334)Beijing Municipal Administration of Hospitals Incubating Program(No.PX2024002,PX2020001)Capital Fund for Health Development Scientific Research(No.2024-2-2028)Beijing Municipal Science&Technology Commission AI+Health Collaborative Innovation Cultivation Project(No.Z241100007724004)Research Ward Excellence Program of Beijing Municipal Health Commission(No.BRWEP2024W162020100,BRWEP2024W162020112,BRWEP2024W162020114)Excellent Plan for Capital Medicine Scientific and Technological Innovation Achievement Transformation Promotion Plan(No.YC202401QX0824)Clinical Scientific Research Fund of Beijing Integrated Medical Association[No.ZHKY-2025-1869(B012)]。
文摘With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Laparoscopic-endoscopic cooperative surgery combined with sentinel lymph node navigation surgery(LECSSNNS)has drawn increasing interest because of its dual benefits of minimal invasiveness and organ function preservation.However,robust evidence-based support for guiding clinical implementation remains limited.To address this gap,we systematically evaluated available studies on the clinical application of LECS-SNNS in EGC and integrated expert insights to formulate 20 recommendations.These included preoperative assessment,surgical techniques,intraoperative endoscopic procedures,pathological evaluation,postoperative care,and follow-up.This consensus aimed to provide comprehensive guidance for the standardized application of LECS-SNNS,thereby advancing precise,minimally invasive,and function-preserving treatment for EGC.
基金supported in part by the National Natural Science Foundation of China(No.42271446)in part by the Tianjin Key Laboratory of Rail Transit Navigation Positioning and Spatio-Temporary Big Data Technology,China(No.TKL2024B13)in part by the Science and Technology Program of Tianjin,China(No.24YFYSHZ00080)。
文摘The selection of a suitable navigation area is pivotal in aircraft scene matching guidance technology.This study addresses the challenge of identifying suitable reference image ranges for precise scene matching,which is crucial for enhancing aircraft positioning accuracy.Traditional methods for image matchability analysis are often limited by their reliance on manual feature parameter design and threshold-based filtering,resulting in suboptimal accuracy and efficiency.This paper proposes a novel network architecture for selecting suitable navigation areas using image Matching Level Segmentation(MLSNet).The approach involves two key innovations:a method for generating segmentation labels that quantify matchability levels and an end-to-end network architecture for rapid and precise prediction of reference image matchability segmentation maps.The network includes two core modules:the saliency analysis module uses multi-layer convolutional networks to accurately detect image saliency features across various levels and scales;the multidimensional attention module utilizes attention mechanisms to focus on feature channels and spatial neighborhood scenes to assess the image’s matchability.Our method was rigorously tested on an extensive collection of remote sensing images,where it was benchmarked against a range of both traditional and cutting-edge deep learning methods.The findings indicate that MLSNet is significantly superior to traditional methods in accuracy and efficiency of matchability analysis,and is also relatively ahead of state-of-the-art deep learning models.
