In this study,a non-tensor product B-spline algorithm is applied to the search space of the registration process,and a new method of image non-rigid registration is proposed.The tensor product B-spline is a function d...In this study,a non-tensor product B-spline algorithm is applied to the search space of the registration process,and a new method of image non-rigid registration is proposed.The tensor product B-spline is a function defined in the two directions of x and y,while the non-tensor product B-spline S^(1/2)(Δ_(mn)^((2)))is defined in four directions on the 2-type triangulation.For certain problems,using non-tensor product B-splines to describe the non-rigid deformation of an image can more accurately extract the four-directional information of the image,thereby describing the global or local non-rigid deformation of the image in more directions.Indeed,it provides a method to solve the problem of image deformation in multiple directions.In addition,the region of interest of medical images is irregular,and usually no value exists on the boundary triangle.The value of the basis function of the non-tensor product B-spline on the boundary triangle is only 0.The algorithm process is optimized.The algorithm performs completely automatic non-rigid registration of computed tomography and magnetic resonance imaging images of patients.In particular,this study compares the performance of the proposed algorithm with the tensor product B-spline registration algorithm.The results elucidate that the proposed algorithm clearly improves the accuracy.展开更多
The purpose of the study was to evaluate the effect of motion compensation by non-rigid registration combined with the Karhunen-Loeve Transform (KLT) filter on the signal to noise (SNR) and contrast-to-noise ratio (CN...The purpose of the study was to evaluate the effect of motion compensation by non-rigid registration combined with the Karhunen-Loeve Transform (KLT) filter on the signal to noise (SNR) and contrast-to-noise ratio (CNR) of hybrid gradient-echo echoplanar (GRE-EPI) first-pass myocardial perfusion imaging. Twenty one consecutive first-pass adenosine stress perfusion MR data sets interpreted positive for ischemia or infarction were processed by non-rigid Registration followed by KLT filtering. SNR and CNR were measured in abnormal and normal myocardium in unfiltered and KLT filtered images following nonrigid registration to compensate for respiratory and other motions. Image artifacts introduced by filtering in registered and nonregistered images were evaluated by two observers. There was a statistically sig- nificant increase in both SNR and CNR between normal and abnormal myocardium with KLT filtering (mean SNR increased by 62.18% ± 21.05% and mean CNR increased by 58.84% ± 18.06%;p = 0.01). Motion correction prior to KLT filtering reduced significantly the occurrence of filter induced artifacts (KLT only-artifacts in 42 out of 55 image series vs. registered plus KLT-artifacts in 3 out of 55 image series). In conclusion the combination of non-rigid registration and KLT filtering was shown to increase the SNR and CNR of GRE-EPI perfusion images. Subjective evaluation of image artifacts revealed that prior motion compensation significantly reduced the artifacts introduced by the KLT filtering process.展开更多
A mutual information based 3D non-rigid registration approach was proposed for the registration of deformable CT/MR body abdomen images. The Parzen Windows Density Estimation (PWDE) method is adopted to calculate the ...A mutual information based 3D non-rigid registration approach was proposed for the registration of deformable CT/MR body abdomen images. The Parzen Windows Density Estimation (PWDE) method is adopted to calculate the mutual information between the two modals of CT and MRI abdomen images. By maximizing MI between the CT and MR volume images, the overlapping part of them reaches the biggest, which means that the two body images of CT and MR matches best to each other. Visible Human Project (VHP) Male abdomen CT and MRI Data are used as experimental data sets. The experimental results indicate that this approach of non-rigid 3D registration of CT/MR body abdominal images can be achieved effectively and automatically, without any prior processing procedures such as segmentation and feature extraction, but has a main drawback of very long computation time.展开更多
This study summarizes the examination data of registration labels for ordinary cosmetics in Beijing from May 2021 to April 2024.It analyzes and categorizes the issues identified during label evaluations,explores the u...This study summarizes the examination data of registration labels for ordinary cosmetics in Beijing from May 2021 to April 2024.It analyzes and categorizes the issues identified during label evaluations,explores the underlying causes,and proposes regulatory countermeasures and recommendations for registrants,regulatory authorities,and social organizations.The objective is to offer practical insights and regulatory guidance to support the enhancement of cosmetic registration and regulatory standards.展开更多
Objective To put forward some suggestions for improving the registration and regulation,the efficiency of evaluation,and approval of biosimilar in China so as to promote the development of biopharmaceutical industry a...Objective To put forward some suggestions for improving the registration and regulation,the efficiency of evaluation,and approval of biosimilar in China so as to promote the development of biopharmaceutical industry and increase the accessibility of therapeutic drugs in China.Methods Literature related to the registration and regulation,evaluation and approval of biosimilars were sorted out to analyze the differences in China and the USA.Results and Conclusion Based on the analysis of the current situation of registration and regulation of biosimilars between China and the USA,it is suggested to improve the registration and regulation of biosimilars in China from the following four aspects:Establishing a biosimilar regulatory department,expanding the professional evaluation personnel,scientifically simplifying the registration and approval procedures,and constantly refining the types of communication meetings.展开更多
Objective To provide a theoretical basis for the adjustment of the registration classification of China’s biological products,and to establish a continuously improved registration classification system.Methods Based ...Objective To provide a theoretical basis for the adjustment of the registration classification of China’s biological products,and to establish a continuously improved registration classification system.Methods Based on literature research,the specific classification methods,classification principles and considerations of biological registration in China,the United States and the European Union were studied to form a complete comparative analysis.Results and Conclusion It is recommended that the division between therapeutic and preventive use should be removed from the registration classification of biologics.The therapeutic,preventive and diagnostic use of the product should be limited as part of the product specification,and the registration should be classified according to the development of biotechnology,innovation,modification and bio-similar drugs.In addition,the supervision of registration of advanced therapeutic products should be different from that of traditional biologics.展开更多
Background:Modern acupuncture anesthesia is a combination of Chinese and Western medicine that integrates the theories of acupuncture with anesthesia.However,some clinical studies of acupuncture anesthesia lack specif...Background:Modern acupuncture anesthesia is a combination of Chinese and Western medicine that integrates the theories of acupuncture with anesthesia.However,some clinical studies of acupuncture anesthesia lack specific descriptions of randomization,allocation concealment,and blinding processes,with subsequent systematic reviews indicating a risk of bias.Objective:Clinical trial registration is essential for the enhancement of the quality of clinical trials.This study aims to summarize the status of clinical trial registrations for acupuncture anesthesia listed on the World Health Organization International Clinical Trials Registry Platform(ICTRP).Search strategy:We searched the ICTRP for clinical trials related to acupuncture anesthesia registered between January 1,2001 and May 31,2023.Additionally,related publications were retrieved from PubMed,Cochrane Library,Embase,China National Knowledge Infrastructure,China Science and Technology Journal Database,and Wanfang Data.Registrations and publications were analyzed for consistency in trial design characteristics.Inclusion criteria:Clinical trials that utilized one of several acupuncture-related therapies in combination with pharmacological anesthesia during the perioperative period were eligible for this review.Data extraction and analysis:Data extracted from articles included type of surgical procedure,perioperative symptoms,study methodology,type of intervention,trial recruitment information,and publication information related to clinical enrollment.Results:A total of 166 trials related to acupuncture anesthesia from 21 countries were included in the analysis.The commonly reported symptoms in the included studies were postoperative nausea and vomiting(19.9%)and postoperative pain(13.3%).The concordance between the publications and the trial protocols in the clinical registry records was poor,with only 31.7%of the studies being fully compatible.Inconsistency rates were high for sample size(39.0%,16/41),blinding(36.6%,15/41),and secondary outcome indicators(24.4%,10/41).Conclusion:The volume of acupuncture anesthesia clinical trials registered in international trial registries over the last 20 years is low,with insufficient disclosure of results.Postoperative nausea and vomiting as well as postoperative pain,are the most investigated for acupuncture intervention.展开更多
The geolocation of ground targets by airborne image sensors is an important task for unmanned aerial vehicles or surveillance aircraft.This paper proposes an Iterative Geolocation based on Cross-view Image Registratio...The geolocation of ground targets by airborne image sensors is an important task for unmanned aerial vehicles or surveillance aircraft.This paper proposes an Iterative Geolocation based on Cross-view Image Registration(IGCIR)that can provide real-time target location results with high precision.The proposed method has two key features.First,a cross-view image registration process is introduced,including a projective transformation and a two-stage multi-sensor registration.This process utilizes both gradient information and phase information of cross-view images.This allows the registration process to reach a good balance between matching precision and computational efficiency.By matching the airborne camera view to the preloaded digital map,the geolocation accuracy can reach the accuracy level of the digital map for any ground target appearing in the airborne camera view.Second,the proposed method uses the registration results to perform an iteration process,which compensates for the bias of the strap-down initial navigation module online.Although it is challenging to provide cross-view registration results with high frequency,such an iteration process allows the method to generate real-time,highly accurate location results.The effectiveness of the proposed IGCIR method is verified by a series of flying-test experiments.The results show that the location accuracy of the method can reach 4.18 m(at 10 km standoff distance).展开更多
This paper aims to develop a nonrigid registration method of preoperative and intraoperative thoracoabdominal CT images in computer-assisted interventional surgeries for accurate tumor localization and tissue visualiz...This paper aims to develop a nonrigid registration method of preoperative and intraoperative thoracoabdominal CT images in computer-assisted interventional surgeries for accurate tumor localization and tissue visualization enhancement.However,fine structure registration of complex thoracoabdominal organs and large deformation registration caused by respiratory motion is challenging.To deal with this problem,we propose a 3D multi-scale attention VoxelMorph(MAVoxelMorph)registration network.To alleviate the large deformation problem,a multi-scale axial attention mechanism is utilized by using a residual dilated pyramid pooling for multi-scale feature extraction,and position-aware axial attention for long-distance dependencies between pixels capture.To further improve the large deformation and fine structure registration results,a multi-scale context channel attention mechanism is employed utilizing content information via adjacent encoding layers.Our method was evaluated on four public lung datasets(DIR-Lab dataset,Creatis dataset,Learn2Reg dataset,OASIS dataset)and a local dataset.Results proved that the proposed method achieved better registration performance than current state-of-the-art methods,especially in handling the registration of large deformations and fine structures.It also proved to be fast in 3D image registration,using about 1.5 s,and faster than most methods.Qualitative and quantitative assessments proved that the proposed MA-VoxelMorph has the potential to realize precise and fast tumor localization in clinical interventional surgeries.展开更多
To provide reference for the prevention and control of diseases,pests,and weeds on Zanthoxylum bungeanum Maxim.and the research and development of new pesticide registrations,this paper analyzes the quantity,variety s...To provide reference for the prevention and control of diseases,pests,and weeds on Zanthoxylum bungeanum Maxim.and the research and development of new pesticide registrations,this paper analyzes the quantity,variety structure,dosage forms,and toxicity of pesticides registered on Z.bungeanum in China.The analysis reveals a relatively low quantity of pesticide registrations on Z.bungeanum,with no herbicide registrations;suspension concentrates dominate the dosage forms,and pesticide toxicity is classified as low-toxicity or micro-toxicity;registered pesticides target only rust,anthracnose,scale insects,aphids,and spider mites,while plant growth regulators solely involve growth regulation and shoot control.Given the current status of limited and incomplete pesticide registrations targeting major diseases,pests,and weeds on Z.bungeanum,severe product homogenization,and unknown maximum residue limits,it is recommended to intensify efforts in pesticide registration on Z.bungeanum,actively research and apply green control technologies,strengthen technical training guidance and pesticide supervision enforcement,to promote the healthy development of the industry.展开更多
Airborne LiDAR(Light Detection and Ranging)is an evolving high-tech active remote sensing technology that has the capability to acquire large-area topographic data and can quickly generate DEM(Digital Elevation Model)...Airborne LiDAR(Light Detection and Ranging)is an evolving high-tech active remote sensing technology that has the capability to acquire large-area topographic data and can quickly generate DEM(Digital Elevation Model)products.Combined with image data,this technology can further enrich and extract spatial geographic information.However,practically,due to the limited operating range of airborne LiDAR and the large area of task,it would be necessary to perform registration and stitching process on point clouds of adjacent flight strips.By eliminating grow errors,the systematic errors in the data need to be effectively reduced.Thus,this paper conducts research on point cloud registration methods in urban building areas,aiming to improve the accuracy and processing efficiency of airborne LiDAR data.Meanwhile,an improved post-ICP(Iterative Closest Point)point cloud registration method was proposed in this study to determine the accurate registration and efficient stitching of point clouds,which capable to provide a potential technical support for applicants in related field.展开更多
Objective To study the inheritance and innovation of traditional Chinese medicine,and to offer an insight for the public.Methods Literature review,data retrieval and systematic analysis were used to elaborate and summ...Objective To study the inheritance and innovation of traditional Chinese medicine,and to offer an insight for the public.Methods Literature review,data retrieval and systematic analysis were used to elaborate and summarize the influence of changes in related classification and policy reform of traditional Chinese medicine(TCM)registration on its inheritance and innovation.The study was carried out in the context of the TCM registration related classification and policy reform and evolution on TCM inheritance and innovation.Results and Conclusion TCM registration plays an important role in the inheritance and innovation of TCM,which greatly influences on its inheritance and innovation.The reform of new registration classification respects the law of TCM research and development,reflecting the establishment of the review and approval system in line with the characteristics of TCM inheritance,which promotes the research and development of new drugs.The establishment of the review and approval system also accelerates the marketing transformation of new traditional Chinese medicine.TCM innovation should attach importance to clinical value orientation and improve the scientific connotation of TCM.Meanwhile,the advantage of China’s accession to ICH,PIC/S and other international drug certification organizations should be taken to speed up the construction of international mutual recognition of TCM standardization system,which can provide a broader path for the inheritance and innovation of TCM in the new era.展开更多
A mutual information-based non-rigid medical image registration algorithm is presented. An approximate function of Hanning windowed sinc is used as kernel function of partial volume (PV) interpolation to estimate the ...A mutual information-based non-rigid medical image registration algorithm is presented. An approximate function of Hanning windowed sinc is used as kernel function of partial volume (PV) interpolation to estimate the joint histogram, which is the key to calculating the mutual information. And a new method is proposed to compute the gradient of mutual information with respect to the model parameters. The transformation of object is modeled by a free-form deformation (FFD) based on B-splines. The experiments on 3D synthetic and real image data show that the algorithm can converge at the global optimum and restrain the emergency of local extreme.展开更多
In clinical diagnosis of lung disease, registration of lung images from different imaging systems can provide a multi-informative image and improve its diagnostic accuracy. In this study, the original lung images were...In clinical diagnosis of lung disease, registration of lung images from different imaging systems can provide a multi-informative image and improve its diagnostic accuracy. In this study, the original lung images were obtained from computed tomography (CT) and single-photon emission computed tomography (SPECT). After the decomposition of the images using wavelet transform, a non-rigid registration were proposed, in which CT image was used as the reference image and SPECT image was used as the floating image. In registration, the mutual information between the reference and floating images was calculated in the process of translation, rotation and elastic transformation. At last, the result of the registration was evaluated by the edges of the bone, muscle, thorax and lung tissues in CT and SPECT images. It showed an accuracy registration between lung CT and SPECT images.展开更多
Optical flow estimation in human facial video,which provides 2D correspondences between adjacent frames,is a fundamental pre-processing step for many applications,like facial expression capture and recognition.However...Optical flow estimation in human facial video,which provides 2D correspondences between adjacent frames,is a fundamental pre-processing step for many applications,like facial expression capture and recognition.However,it is quite challenging as human facial images contain large areas of similar textures,rich expressions,and large rotations.These characteristics also result in the scarcity of large,annotated realworld datasets.We propose a robust and accurate method to learn facial optical flow in a self-supervised manner.Specifically,we utilize various shape priors,including face depth,landmarks,and parsing,to guide the self-supervised learning task via a differentiable nonrigid registration framework.Extensive experiments demonstrate that our method achieves remarkable improvements for facial optical flow estimation in the presence of significant expressions and large rotations.展开更多
Non-rigid registration of point clouds is still far from stable,especially for the largely deformed one.Sparse initial correspondences are often adopted to facilitate the process.However,there are few studies on how t...Non-rigid registration of point clouds is still far from stable,especially for the largely deformed one.Sparse initial correspondences are often adopted to facilitate the process.However,there are few studies on how to build them automatically.Therefore,in this paper,we propose a robust method to compute such priors automatically,where a global and local combined strategy is adopted.These priors in different degrees of deformation are obtained by the locally geometrical-consistent point matches from the globally structural-consistent region correspondences.To further utilize the matches,this paper also proposes a novel registration method based on the Coherent Point Drift framework.This method takes both the spatial proximity and local structural consistency of the priors as supervision of the registration process and thus obtains a robust alignment for clouds with significantly different deformations.Qualitative and quantitative experiments demonstrate the advantages of the proposed method.展开更多
The traditional pipeline for non-rigid registration is to iteratively update the correspondence and alignment such that the transformed source surface aligns well with the target surface.Among the pipeline,the corresp...The traditional pipeline for non-rigid registration is to iteratively update the correspondence and alignment such that the transformed source surface aligns well with the target surface.Among the pipeline,the correspondence construction and iterative manner are key to the results,while existing strategies might result in local optima.In this paper,we adopt the widely used deformation graph-based representation,while replacing some key modules with neural learning-based strategies.Specifically,we design a neural network to predict the correspondence and its reliability confidence rather than the strategies like nearest neighbor search and pair rejection.Besides,we adopt the GRU-based recurrent network for iterative refinement,which is more robust than the traditional strategy.The model is trained in a self-supervised manner and thus can be used for arbitrary datasets without ground-truth.Extensive experiments demonstrate that our proposed method outperforms the state-of-the-art methods by a large margin.展开更多
Registrations based on the manual placement of spherical targets are still being employed by many professionals in the industry.However,the placement of those targets usually relies solely on personal experience witho...Registrations based on the manual placement of spherical targets are still being employed by many professionals in the industry.However,the placement of those targets usually relies solely on personal experience without scientific evidence supported by numerical analysis.This paper presents a comprehensive investigation,based on Monte Carlo simulation,into determining the optimal number and positions for efficient target placement in typical scenes consisting of a pair of facades.It demonstrates new check-up statistical rules and geometrical constraints that can effectively extract and analyze massive simulations of unregistered point clouds and their corresponding registrations.More than 6×10^(7) sets of the registrations were simulated,whereas more than IOO registrations with real data were used to verify the results of simulation.The results indicated that using five spherical targets is the best choice for the registration of a large typical registration site consisting of two vertical facades and a ground,when there is only a box set of spherical targets available.As a result,the users can avoid placing extra targets to achieve insignificant improvements in registration accuracy.The results also suggest that the higher registration accuracy can be obtained when the ratio between the facade-to-target distance and target-to-scanner distance is approximately 3:2.Therefore,the targets should be placed closer to the scanner rather than in the middle between the facades and the scanner,contradicting to the traditional thought. Besides,the results reveal that the accuracy can be increased by setting the largest projected triangular area of the targets to be large.展开更多
Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of tissue.Convolutional neural network(CNN)and generative adversarial ne...Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of tissue.Convolutional neural network(CNN)and generative adversarial network(GAN)are pivotal inmedical image registration.However,existing methods often struggle with severe interference and deformation,as seen in histological images of conditions like Cushing’s disease.We argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator inGAN.In this study,we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image registration.To begin with,the discriminators of two GANs are embedded as a new dual parallel feature extraction module into the unsupervised registration networks,characterized by implicitly extracting feature descriptors of specific modalities.Additionally,modal feature description layers and registration layers collaborate in unsupervised optimization,facilitating faster convergence and more precise results.Lastly,experiments and evaluations were conducted on the registration of the Mixed National Institute of Standards and Technology database(MNIST),eight publicly available datasets of histological sections and the Clustering-Registration-Classification-Segmentation(CRCS)dataset on the Cushing’s disease.Experimental results demonstrate that our proposed GAN-DIRNet method surpasses existing approaches like DIRNet in terms of both registration accuracy and time efficiency,while also exhibiting robustness across different image types.展开更多
Many deep learning-based registration methods rely on a single-stream encoder-decoder network for computing deformation fields between 3D volumes.However,these methods often lack constraint information and overlook se...Many deep learning-based registration methods rely on a single-stream encoder-decoder network for computing deformation fields between 3D volumes.However,these methods often lack constraint information and overlook semantic consistency,limiting their performance.To address these issues,we present a novel approach for medical image registration called theDual-VoxelMorph,featuring a dual-channel cross-constraint network.This innovative network utilizes both intensity and segmentation images,which share identical semantic information and feature representations.Two encoder-decoder structures calculate deformation fields for intensity and segmentation images,as generated by the dual-channel cross-constraint network.This design facilitates bidirectional communication between grayscale and segmentation information,enabling the model to better learn the corresponding grayscale and segmentation details of the same anatomical structures.To ensure semantic and directional consistency,we introduce constraints and apply the cosine similarity function to enhance semantic consistency.Evaluation on four public datasets demonstrates superior performance compared to the baselinemethod,achieving Dice scores of 79.9%,64.5%,69.9%,and 63.5%for OASIS-1,OASIS-3,LPBA40,and ADNI,respectively.展开更多
基金This research was funded by National Natural Science Foundation of China,No.61702184Ministry of Education Production University Cooperation Education Project,No.201802305012Tangshan Innovation Team Project,No.18130209 B.
文摘In this study,a non-tensor product B-spline algorithm is applied to the search space of the registration process,and a new method of image non-rigid registration is proposed.The tensor product B-spline is a function defined in the two directions of x and y,while the non-tensor product B-spline S^(1/2)(Δ_(mn)^((2)))is defined in four directions on the 2-type triangulation.For certain problems,using non-tensor product B-splines to describe the non-rigid deformation of an image can more accurately extract the four-directional information of the image,thereby describing the global or local non-rigid deformation of the image in more directions.Indeed,it provides a method to solve the problem of image deformation in multiple directions.In addition,the region of interest of medical images is irregular,and usually no value exists on the boundary triangle.The value of the basis function of the non-tensor product B-spline on the boundary triangle is only 0.The algorithm process is optimized.The algorithm performs completely automatic non-rigid registration of computed tomography and magnetic resonance imaging images of patients.In particular,this study compares the performance of the proposed algorithm with the tensor product B-spline registration algorithm.The results elucidate that the proposed algorithm clearly improves the accuracy.
文摘The purpose of the study was to evaluate the effect of motion compensation by non-rigid registration combined with the Karhunen-Loeve Transform (KLT) filter on the signal to noise (SNR) and contrast-to-noise ratio (CNR) of hybrid gradient-echo echoplanar (GRE-EPI) first-pass myocardial perfusion imaging. Twenty one consecutive first-pass adenosine stress perfusion MR data sets interpreted positive for ischemia or infarction were processed by non-rigid Registration followed by KLT filtering. SNR and CNR were measured in abnormal and normal myocardium in unfiltered and KLT filtered images following nonrigid registration to compensate for respiratory and other motions. Image artifacts introduced by filtering in registered and nonregistered images were evaluated by two observers. There was a statistically sig- nificant increase in both SNR and CNR between normal and abnormal myocardium with KLT filtering (mean SNR increased by 62.18% ± 21.05% and mean CNR increased by 58.84% ± 18.06%;p = 0.01). Motion correction prior to KLT filtering reduced significantly the occurrence of filter induced artifacts (KLT only-artifacts in 42 out of 55 image series vs. registered plus KLT-artifacts in 3 out of 55 image series). In conclusion the combination of non-rigid registration and KLT filtering was shown to increase the SNR and CNR of GRE-EPI perfusion images. Subjective evaluation of image artifacts revealed that prior motion compensation significantly reduced the artifacts introduced by the KLT filtering process.
基金An international cooperation project between Shanghai Jiaotong U niversity and Hong Kong Polytechnic University
文摘A mutual information based 3D non-rigid registration approach was proposed for the registration of deformable CT/MR body abdomen images. The Parzen Windows Density Estimation (PWDE) method is adopted to calculate the mutual information between the two modals of CT and MRI abdomen images. By maximizing MI between the CT and MR volume images, the overlapping part of them reaches the biggest, which means that the two body images of CT and MR matches best to each other. Visible Human Project (VHP) Male abdomen CT and MRI Data are used as experimental data sets. The experimental results indicate that this approach of non-rigid 3D registration of CT/MR body abdominal images can be achieved effectively and automatically, without any prior processing procedures such as segmentation and feature extraction, but has a main drawback of very long computation time.
文摘This study summarizes the examination data of registration labels for ordinary cosmetics in Beijing from May 2021 to April 2024.It analyzes and categorizes the issues identified during label evaluations,explores the underlying causes,and proposes regulatory countermeasures and recommendations for registrants,regulatory authorities,and social organizations.The objective is to offer practical insights and regulatory guidance to support the enhancement of cosmetic registration and regulatory standards.
文摘Objective To put forward some suggestions for improving the registration and regulation,the efficiency of evaluation,and approval of biosimilar in China so as to promote the development of biopharmaceutical industry and increase the accessibility of therapeutic drugs in China.Methods Literature related to the registration and regulation,evaluation and approval of biosimilars were sorted out to analyze the differences in China and the USA.Results and Conclusion Based on the analysis of the current situation of registration and regulation of biosimilars between China and the USA,it is suggested to improve the registration and regulation of biosimilars in China from the following four aspects:Establishing a biosimilar regulatory department,expanding the professional evaluation personnel,scientifically simplifying the registration and approval procedures,and constantly refining the types of communication meetings.
文摘Objective To provide a theoretical basis for the adjustment of the registration classification of China’s biological products,and to establish a continuously improved registration classification system.Methods Based on literature research,the specific classification methods,classification principles and considerations of biological registration in China,the United States and the European Union were studied to form a complete comparative analysis.Results and Conclusion It is recommended that the division between therapeutic and preventive use should be removed from the registration classification of biologics.The therapeutic,preventive and diagnostic use of the product should be limited as part of the product specification,and the registration should be classified according to the development of biotechnology,innovation,modification and bio-similar drugs.In addition,the supervision of registration of advanced therapeutic products should be different from that of traditional biologics.
基金supported by grants from Shanghai Municipal Health Commission and Shanghai Municipal Administration of TCM—Standardization of TCM in 2023“Clinical Practice Guide for Combined Acupuncture-Drug Anesthesia”(No.2023JS05)Shanghai Clinical Medical Research Center of Acupuncture and Moxibustion(No.20MC1920500)+1 种基金Shanghai master Chinese medicine practitioners academic experience research studio construction project(No.SHGZS-202212)Shanghai Key Clinical Specialties 2019 Accreditation Program(No.shslczdzk04701)。
文摘Background:Modern acupuncture anesthesia is a combination of Chinese and Western medicine that integrates the theories of acupuncture with anesthesia.However,some clinical studies of acupuncture anesthesia lack specific descriptions of randomization,allocation concealment,and blinding processes,with subsequent systematic reviews indicating a risk of bias.Objective:Clinical trial registration is essential for the enhancement of the quality of clinical trials.This study aims to summarize the status of clinical trial registrations for acupuncture anesthesia listed on the World Health Organization International Clinical Trials Registry Platform(ICTRP).Search strategy:We searched the ICTRP for clinical trials related to acupuncture anesthesia registered between January 1,2001 and May 31,2023.Additionally,related publications were retrieved from PubMed,Cochrane Library,Embase,China National Knowledge Infrastructure,China Science and Technology Journal Database,and Wanfang Data.Registrations and publications were analyzed for consistency in trial design characteristics.Inclusion criteria:Clinical trials that utilized one of several acupuncture-related therapies in combination with pharmacological anesthesia during the perioperative period were eligible for this review.Data extraction and analysis:Data extracted from articles included type of surgical procedure,perioperative symptoms,study methodology,type of intervention,trial recruitment information,and publication information related to clinical enrollment.Results:A total of 166 trials related to acupuncture anesthesia from 21 countries were included in the analysis.The commonly reported symptoms in the included studies were postoperative nausea and vomiting(19.9%)and postoperative pain(13.3%).The concordance between the publications and the trial protocols in the clinical registry records was poor,with only 31.7%of the studies being fully compatible.Inconsistency rates were high for sample size(39.0%,16/41),blinding(36.6%,15/41),and secondary outcome indicators(24.4%,10/41).Conclusion:The volume of acupuncture anesthesia clinical trials registered in international trial registries over the last 20 years is low,with insufficient disclosure of results.Postoperative nausea and vomiting as well as postoperative pain,are the most investigated for acupuncture intervention.
基金supported by the National Level Project of China(No.52-L0D01-0613-20/22)。
文摘The geolocation of ground targets by airborne image sensors is an important task for unmanned aerial vehicles or surveillance aircraft.This paper proposes an Iterative Geolocation based on Cross-view Image Registration(IGCIR)that can provide real-time target location results with high precision.The proposed method has two key features.First,a cross-view image registration process is introduced,including a projective transformation and a two-stage multi-sensor registration.This process utilizes both gradient information and phase information of cross-view images.This allows the registration process to reach a good balance between matching precision and computational efficiency.By matching the airborne camera view to the preloaded digital map,the geolocation accuracy can reach the accuracy level of the digital map for any ground target appearing in the airborne camera view.Second,the proposed method uses the registration results to perform an iteration process,which compensates for the bias of the strap-down initial navigation module online.Although it is challenging to provide cross-view registration results with high frequency,such an iteration process allows the method to generate real-time,highly accurate location results.The effectiveness of the proposed IGCIR method is verified by a series of flying-test experiments.The results show that the location accuracy of the method can reach 4.18 m(at 10 km standoff distance).
基金supported in part by the National Natural Science Foundation of China[62301374]Hubei Provincial Natural Science Foundation of China[2022CFB804]+2 种基金Hubei Provincial Education Research Project[B2022057]the Youths Science Foundation of Wuhan Institute of Technology[K202240]the 15th Graduate Education Innovation Fund of Wuhan Institute of Technology[CX2023295].
文摘This paper aims to develop a nonrigid registration method of preoperative and intraoperative thoracoabdominal CT images in computer-assisted interventional surgeries for accurate tumor localization and tissue visualization enhancement.However,fine structure registration of complex thoracoabdominal organs and large deformation registration caused by respiratory motion is challenging.To deal with this problem,we propose a 3D multi-scale attention VoxelMorph(MAVoxelMorph)registration network.To alleviate the large deformation problem,a multi-scale axial attention mechanism is utilized by using a residual dilated pyramid pooling for multi-scale feature extraction,and position-aware axial attention for long-distance dependencies between pixels capture.To further improve the large deformation and fine structure registration results,a multi-scale context channel attention mechanism is employed utilizing content information via adjacent encoding layers.Our method was evaluated on four public lung datasets(DIR-Lab dataset,Creatis dataset,Learn2Reg dataset,OASIS dataset)and a local dataset.Results proved that the proposed method achieved better registration performance than current state-of-the-art methods,especially in handling the registration of large deformations and fine structures.It also proved to be fast in 3D image registration,using about 1.5 s,and faster than most methods.Qualitative and quantitative assessments proved that the proposed MA-VoxelMorph has the potential to realize precise and fast tumor localization in clinical interventional surgeries.
基金Supported by Sichuan Province Zanthoxylum bungeanum Maxim.Innovation Team Project"Green Control of Diseases and Weeds on Zanthoxylum bungeanum Maxim."Institute-Local Cooperation Project"Demonstration of Chemical Fertilizer and Pesticide Reduction Techniques in Hongya County(2024-2026)".
文摘To provide reference for the prevention and control of diseases,pests,and weeds on Zanthoxylum bungeanum Maxim.and the research and development of new pesticide registrations,this paper analyzes the quantity,variety structure,dosage forms,and toxicity of pesticides registered on Z.bungeanum in China.The analysis reveals a relatively low quantity of pesticide registrations on Z.bungeanum,with no herbicide registrations;suspension concentrates dominate the dosage forms,and pesticide toxicity is classified as low-toxicity or micro-toxicity;registered pesticides target only rust,anthracnose,scale insects,aphids,and spider mites,while plant growth regulators solely involve growth regulation and shoot control.Given the current status of limited and incomplete pesticide registrations targeting major diseases,pests,and weeds on Z.bungeanum,severe product homogenization,and unknown maximum residue limits,it is recommended to intensify efforts in pesticide registration on Z.bungeanum,actively research and apply green control technologies,strengthen technical training guidance and pesticide supervision enforcement,to promote the healthy development of the industry.
基金Guangxi Key Laboratory of Spatial Information and Geomatics(21-238-21-12)Guangxi Young and Middle-aged Teachers’Research Fundamental Ability Enhancement Project(2023KY1196).
文摘Airborne LiDAR(Light Detection and Ranging)is an evolving high-tech active remote sensing technology that has the capability to acquire large-area topographic data and can quickly generate DEM(Digital Elevation Model)products.Combined with image data,this technology can further enrich and extract spatial geographic information.However,practically,due to the limited operating range of airborne LiDAR and the large area of task,it would be necessary to perform registration and stitching process on point clouds of adjacent flight strips.By eliminating grow errors,the systematic errors in the data need to be effectively reduced.Thus,this paper conducts research on point cloud registration methods in urban building areas,aiming to improve the accuracy and processing efficiency of airborne LiDAR data.Meanwhile,an improved post-ICP(Iterative Closest Point)point cloud registration method was proposed in this study to determine the accurate registration and efficient stitching of point clouds,which capable to provide a potential technical support for applicants in related field.
文摘Objective To study the inheritance and innovation of traditional Chinese medicine,and to offer an insight for the public.Methods Literature review,data retrieval and systematic analysis were used to elaborate and summarize the influence of changes in related classification and policy reform of traditional Chinese medicine(TCM)registration on its inheritance and innovation.The study was carried out in the context of the TCM registration related classification and policy reform and evolution on TCM inheritance and innovation.Results and Conclusion TCM registration plays an important role in the inheritance and innovation of TCM,which greatly influences on its inheritance and innovation.The reform of new registration classification respects the law of TCM research and development,reflecting the establishment of the review and approval system in line with the characteristics of TCM inheritance,which promotes the research and development of new drugs.The establishment of the review and approval system also accelerates the marketing transformation of new traditional Chinese medicine.TCM innovation should attach importance to clinical value orientation and improve the scientific connotation of TCM.Meanwhile,the advantage of China’s accession to ICH,PIC/S and other international drug certification organizations should be taken to speed up the construction of international mutual recognition of TCM standardization system,which can provide a broader path for the inheritance and innovation of TCM in the new era.
基金Supported bythe National Basic Research Programof China ("973"Program) (No2003CB716103)Key Project of Shanghai Scienceand Technology Committee(No05DZ19509)
文摘A mutual information-based non-rigid medical image registration algorithm is presented. An approximate function of Hanning windowed sinc is used as kernel function of partial volume (PV) interpolation to estimate the joint histogram, which is the key to calculating the mutual information. And a new method is proposed to compute the gradient of mutual information with respect to the model parameters. The transformation of object is modeled by a free-form deformation (FFD) based on B-splines. The experiments on 3D synthetic and real image data show that the algorithm can converge at the global optimum and restrain the emergency of local extreme.
基金supported by National Key Basic Research Program(973 Project)(Project No.20152015CB931802)National Natural Scientific Foundation of China(Grant Nos.81225010,81028009,and 31170961)+1 种基金863 project of China(Project No.2012AA022703 and 2014AA020700)Shanghai Science and Technology Fund(13NM1401500).
文摘In clinical diagnosis of lung disease, registration of lung images from different imaging systems can provide a multi-informative image and improve its diagnostic accuracy. In this study, the original lung images were obtained from computed tomography (CT) and single-photon emission computed tomography (SPECT). After the decomposition of the images using wavelet transform, a non-rigid registration were proposed, in which CT image was used as the reference image and SPECT image was used as the floating image. In registration, the mutual information between the reference and floating images was calculated in the process of translation, rotation and elastic transformation. At last, the result of the registration was evaluated by the edges of the bone, muscle, thorax and lung tissues in CT and SPECT images. It showed an accuracy registration between lung CT and SPECT images.
基金This work was supported by National Natural Science Foundation of China(No.62122071)the Youth Innovation Promotion Association CAS(No.2018495)+1 种基金the Fundamental Research Funds for the Central Universities(No.WK3470000021)through the Alibaba Innovation Research Program(AIR).
文摘Optical flow estimation in human facial video,which provides 2D correspondences between adjacent frames,is a fundamental pre-processing step for many applications,like facial expression capture and recognition.However,it is quite challenging as human facial images contain large areas of similar textures,rich expressions,and large rotations.These characteristics also result in the scarcity of large,annotated realworld datasets.We propose a robust and accurate method to learn facial optical flow in a self-supervised manner.Specifically,we utilize various shape priors,including face depth,landmarks,and parsing,to guide the self-supervised learning task via a differentiable nonrigid registration framework.Extensive experiments demonstrate that our method achieves remarkable improvements for facial optical flow estimation in the presence of significant expressions and large rotations.
基金supported by Natural Science Foundation of Anhui Province (2108085MF210,1908085MF187)Key Natural Science Fund of Department of Eduction of Anhui Province (KJ2021A0042)Natural Social Science Foundation of China (19BTY091).
文摘Non-rigid registration of point clouds is still far from stable,especially for the largely deformed one.Sparse initial correspondences are often adopted to facilitate the process.However,there are few studies on how to build them automatically.Therefore,in this paper,we propose a robust method to compute such priors automatically,where a global and local combined strategy is adopted.These priors in different degrees of deformation are obtained by the locally geometrical-consistent point matches from the globally structural-consistent region correspondences.To further utilize the matches,this paper also proposes a novel registration method based on the Coherent Point Drift framework.This method takes both the spatial proximity and local structural consistency of the priors as supervision of the registration process and thus obtains a robust alignment for clouds with significantly different deformations.Qualitative and quantitative experiments demonstrate the advantages of the proposed method.
基金supported by National Natural Science Foundation of China(No.62122071)the Youth Innovation Promotion Association CAS(No.2018495)“the Fundamental Research Funds for the Central Universities”(No.WK3470000021).
文摘The traditional pipeline for non-rigid registration is to iteratively update the correspondence and alignment such that the transformed source surface aligns well with the target surface.Among the pipeline,the correspondence construction and iterative manner are key to the results,while existing strategies might result in local optima.In this paper,we adopt the widely used deformation graph-based representation,while replacing some key modules with neural learning-based strategies.Specifically,we design a neural network to predict the correspondence and its reliability confidence rather than the strategies like nearest neighbor search and pair rejection.Besides,we adopt the GRU-based recurrent network for iterative refinement,which is more robust than the traditional strategy.The model is trained in a self-supervised manner and thus can be used for arbitrary datasets without ground-truth.Extensive experiments demonstrate that our proposed method outperforms the state-of-the-art methods by a large margin.
基金Key Research and Development Program of Guangdong Province (No.2020B0101130009)
文摘Registrations based on the manual placement of spherical targets are still being employed by many professionals in the industry.However,the placement of those targets usually relies solely on personal experience without scientific evidence supported by numerical analysis.This paper presents a comprehensive investigation,based on Monte Carlo simulation,into determining the optimal number and positions for efficient target placement in typical scenes consisting of a pair of facades.It demonstrates new check-up statistical rules and geometrical constraints that can effectively extract and analyze massive simulations of unregistered point clouds and their corresponding registrations.More than 6×10^(7) sets of the registrations were simulated,whereas more than IOO registrations with real data were used to verify the results of simulation.The results indicated that using five spherical targets is the best choice for the registration of a large typical registration site consisting of two vertical facades and a ground,when there is only a box set of spherical targets available.As a result,the users can avoid placing extra targets to achieve insignificant improvements in registration accuracy.The results also suggest that the higher registration accuracy can be obtained when the ratio between the facade-to-target distance and target-to-scanner distance is approximately 3:2.Therefore,the targets should be placed closer to the scanner rather than in the middle between the facades and the scanner,contradicting to the traditional thought. Besides,the results reveal that the accuracy can be increased by setting the largest projected triangular area of the targets to be large.
文摘Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of tissue.Convolutional neural network(CNN)and generative adversarial network(GAN)are pivotal inmedical image registration.However,existing methods often struggle with severe interference and deformation,as seen in histological images of conditions like Cushing’s disease.We argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator inGAN.In this study,we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image registration.To begin with,the discriminators of two GANs are embedded as a new dual parallel feature extraction module into the unsupervised registration networks,characterized by implicitly extracting feature descriptors of specific modalities.Additionally,modal feature description layers and registration layers collaborate in unsupervised optimization,facilitating faster convergence and more precise results.Lastly,experiments and evaluations were conducted on the registration of the Mixed National Institute of Standards and Technology database(MNIST),eight publicly available datasets of histological sections and the Clustering-Registration-Classification-Segmentation(CRCS)dataset on the Cushing’s disease.Experimental results demonstrate that our proposed GAN-DIRNet method surpasses existing approaches like DIRNet in terms of both registration accuracy and time efficiency,while also exhibiting robustness across different image types.
基金National Natural Science Foundation of China(Grant Nos.62171130,62172197,61972093)the Natural Science Foundation of Fujian Province(Grant Nos.2020J01573,2022J01131257,2022J01607)+3 种基金Fujian University Industry University Research Joint Innovation Project(No.2022H6006)in part by the Fund of Cloud Computing and BigData for SmartAgriculture(GrantNo.117-612014063)NationalNatural Science Foundation of China(Grant No.62301160)Nature Science Foundation of Fujian Province(Grant No.2022J01607).
文摘Many deep learning-based registration methods rely on a single-stream encoder-decoder network for computing deformation fields between 3D volumes.However,these methods often lack constraint information and overlook semantic consistency,limiting their performance.To address these issues,we present a novel approach for medical image registration called theDual-VoxelMorph,featuring a dual-channel cross-constraint network.This innovative network utilizes both intensity and segmentation images,which share identical semantic information and feature representations.Two encoder-decoder structures calculate deformation fields for intensity and segmentation images,as generated by the dual-channel cross-constraint network.This design facilitates bidirectional communication between grayscale and segmentation information,enabling the model to better learn the corresponding grayscale and segmentation details of the same anatomical structures.To ensure semantic and directional consistency,we introduce constraints and apply the cosine similarity function to enhance semantic consistency.Evaluation on four public datasets demonstrates superior performance compared to the baselinemethod,achieving Dice scores of 79.9%,64.5%,69.9%,and 63.5%for OASIS-1,OASIS-3,LPBA40,and ADNI,respectively.
