GAN-DIRNet:A Novel Deformable Image Registration Approach for Multimodal Histological Images

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.

Nonlinear Registration of Brain Magnetic Resonance Images with Cross Constraints of Intensity and Structure

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.

A harmonisation approach to traditional Chinese medicine registration in Asian countries

The traditional Chinese medicine(TCM)industry is critical to not only for public health but also for economic growth.According to the European Union(EU)directives,under the EU framework for(traditional)herbal medicinal products,herbal medicines with long history of use can be registered in EU.However,there is a condition in this directive in which only those that have at least 10e15 years in the EU market are accepted for registration and/or marketing authorization.In author opinion,the condition of 10-15 years of use in EU countries set within the EU regulatory framework is with consideration of the genetic differences which can result in variation in adverse drug responses among different world populations.With this concept in mind,it is reasonable to project the principal of the EU directive to the Asian countries where TCM is originated.Countries like China,Singapore,Japan and South Korea that have well established drug registration framework are in best position in executing the best practice and facilitate harmonization of registration for TCM within the region.Furthermore,the registration process itself allows more safety and efficacy data to be collected systemically before and after product registration/marketing authorization.These are valuable information for future drug development.The therapeutic value of TCM is limitless,it has been left out in the EU regulatory framework,and the opportunity for it to be expanded and carried forward in modern medicines is shadowed by the limited number of TCM that are qualified to be registered under the EU regulatory framework.An early establishment of a harmonized risk-based registration process for TCM in Asian countries is important.This will strengthen the database to substantiate the history of safe use and further preserving and expanding the therapeutic values of TCM within and beyond the Asian region.

Optimization of the Use of Spherical Targets for Point Cloud Registration Using Monte Carlo Simulation

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.

Research Progress and Suggestions on China’s Drug Registration Management Based on CiteSpace Knowledge Maps

Objective To analyze the research status and hot spots in the field of drug registration in China,and to provide some suggestions for the follow-up research.Methods CiteSpace was used to conduct literature quantitative analysis on 684 related articles from 2012 to 2022,and the knowledge map was drawn.Based on this,the main characteristics and development trends of the related studies were summarized.Results and Conclusion The number of articles published was closely related to the regulatory policy of drug registration reform.The authors of these articles did not have good continuity.Besides,research hot spots were closely related to the actual work,which was mainly around the improvement of the review and approval policy,encouraging innovative drug research and development,improving the level of new drug development and other directions.The follow-up studies should further strengthen the continuity of research and inter-agency collaboration.In addition,biomedical registration may become a new research focus in the future.

The Study of Legal Property of Household Registration System in Our Country

From ＂the case that three girls have some fate but have different value＂ to ＂the case that Hai Cheng took a police substation to court with three times＂, currently the household registration system of our country not only plays the role of account registration and account management, but also undertakes the limitation of migration movement, and for the additional functions of the lowest life guarantee, social insurance, compulsory education, employment and other social security benefits, it also makes a difference between local registered permanent residence habitant and nonlocal registered permanent residence habitant. Just because of these additional functions, the household registration system has become complicated, which originally has clear nature. Therefore, only it is necessary to define the legal nature of our country＇s current household registration system, can executive power be supervised and the rights of citizens get relief.

New Path for Integrated Reform of Urban and Rural Household Registration System in the Context of Informationization

In China, household registration system has the problems of unreasonable standard setting and relevant supporting measures failure to keep pace with the development trend. From analysis of current problems and situations, it is believed that household registration system should undertake reform and take a new road by means of informationization. Strengthening informationization management in land, population, education and labor market can better perform urban and rural integration.

China Has a Population of 1.2058 Billion with Household Registration

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Breakthrough and New Projects for Reform of Household Registration System

Under the comprehensive deepening reform and promoting new urbanization,China launched a new round of reform of household registration system.Reform has a major breakthrough in five areas:to implement new urbanization strategy of human-centric,to achieve equalization of basic public services gradually,to break up land rights and rural migrants,to provide protection for family migrants,and to increase financial support by governments.But the reform still faces many difficulties,how to determine the conditions settled by city size is difficult to implement effectively,financial transfer payment system reform is facing enormous diffi culties,as well as the size of the urban population is diffi cult to determine etc.

The Impact of Simulation Education on Self-Efficacy in Pre-Registration Nursing Students

This literature review primarily aims to explore and synthesise the previous studies in simulation education research conducted over the past five years related to the effects of simulation training on the self-efficacy of undergraduate pre-registration nursing students. The second aim of this study is to explore additional outcome variables that were examined in the previous studies. Five electronic databases were searched systematically. These databases were MEDLINE, CINAHL Plus, Scopus, Embase and PsycINFO. The PICO model was employed to identify the search terms, with a thesaurus being used to provide synonyms. Reference lists of relevant articles were examined and hand searches of journals were also undertaken. The quality of each study was assessed using the Simulation Research Rubric (SRR). A total of 11 studies were included. All studies explored the impact of simulation education on undergraduate pre-registration nursing. Six studies explored nursing students’ competence and performance and two papers examined their critical thinking. Problem solving, learning motivation, communication skills and knowledge acquisition were examined once. The majority of studies indicated that simulation training has a positive impact on pre-registration nursing students’ self-efficacy and other outcome variables. Furthermore, the study results indicate that simulation training is more dependable than traditional training, and students were extremely satisfied with the simulation training. However, most of the studies included in this review had several gaps, including study design, sample size and dissimilarities between the scales used. Further research with large samples, reliable and valid instruments, and outcomes measures (such as critical thinking and transferability of skills) is required to provide better insight into the effectiveness of simulation in undergraduate nursing education. .

Automated Registration for Infrared Image Based on Wavelet Analysis

To develop a quick, accurate and antinoise automated image registration technique for infrared images, the wavelet analysis technique was used to extract the feature points in two images followed by the compensation for input image with angle difference between them. A hi erarchical feature matching algorithm was adopted to get the final transform parameters between the two images. The simulation results for two infrared images show that the method can effectively, quickly and accurately register images and be antinoise to some extent.

Sensor Registration in Asynchronous Data Fusion

To find an effective method to estimate and remove the registration error in asynchronous multisensor system, Kalman filtering technique and least squares approach have been proposed to estimate and remove sensor bias and sensor frame tilt errors in multisensor systems with asynchronous data. Simulation results is presented to demonstrate the performance of these approaches. The least squares approach can compress measurements to any time. The Kalman filter algorithm can detect registration errors and use the information to converge tracks from independent sensors. This is particularly important if the data from the sensors are to be fused.

Kalman Fliter Approach to Multisensor Registration of Moving Platform

Aim To find an effective method to remove the registration error in multi-sensor systems. Methods A Kalman filtering technique was proposed to estimate and remove sensor bias and sensor fare tilt errors in multisensor systems with a moving platform. Results Simulation results are presented to demonstrate the performance of the approach. Conclusion The Kalman filter algorithm am detect registration errors and use this information to converge tracks from independent sensors. This is particularly important if the data from the sensors are to fused.

Projection registration of X-ray image and CT image

A methodology for alignment of an X-ray image and a CT image, based on the Chamfer 3-4 distance transform and simulated annealing optimization algorithm is presented. Firstly, an initial transformation matrix is constructed. For the convenience of computing, geometric models of the X-ray device to reconstruct the calibration matrix are used. Then, by defining the distance between the 3-D protective and the 2-D object image, we optimize this distance matching problem, using the simulated annealing algorithm. This method is also integrated into medical intra-operation, dealing with the data set acquired from 3-D image workstation and active navigation.

IMAGE PANORAMIC MOS AICING WITH GLOBAL AND LOCAL REGISTRATION

Technique s for constructing full view panoramic mosaics from sequences of images are pres ented. The goal of this work is to remove too many limitations for pure panning motion. The best reference block is important for the block-matching method for improving the robustness and performance. It is automatically selected in the h igh-frequency image, which always contains the plenty visible features. In orde r to reduce accumulated registration errors, the global registration using the p hase-correlation matching method with rotation adjustment is applied to the who le sequence of images, which results in an optimal image mosaic with resolving t ranslational or rotational motion. The local registration using the Levenberg-M arquardt iterative non-linear minimization algorithm is applied to compensating for small amounts of motion parallax introduced by translations of the camera a nd other unmodeled distortions, then minimizing the discrepancy after applying t he global registration. The accumulated misregistration errors may cause a visib le gap between the two images. A smoothing filter is introduced for removing the visible artifact.

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

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

A method based on mutual information and gradient information for medical image registration

Mutual information is widely used in medical image registration, because it does not require preprocessing the image. However, the local maximum problem in the registration is insurmountable. We combine mutual information and gradient information to solve this problem and apply it to the non-rigid deformation image registration. To improve the accuracy, we provide some implemental issues, for example, the Powell searching algorithm, gray interpolation and consideration of outlier points. The experimental results show the accuracy of the method and the feasibility in non-rigid medical image registration.