The medical image registration between preoperative three-dimensional (3D) scan data and intraoperative two-dimensional (2D) image is a key technology in the surgical navigation. Most previous methods need to generate 2D digitally reconstructed radiographs (DRR) images from the 3D scan volume data, then use conventional image similarity function for comparison. This procedure includes a large amount of calculation and is difficult to archive real-time processing. In this paper, with using geometric feature and image density mixed characteristics, we proposed a new similarity measure function for fast 2D-3D registration of preoperative CT and intraoperative X-ray images. This algorithm is easy to implement, and the calculation process is very short, while the resulting registration accuracy can meet the clinical use. In addition, the entire calculation process is very suitable for highly parallel numerical calculation by using the algorithm based on CUDA hardware acceleration to satisfy the requirement of real-time application in surgery.
Non-rigid medical image registration is a popular subject in the research areas of the medical image and has an important clinical value. In this paper we put forward an improved algorithm of Demons, together with the conservation of gray model and local structure tensor conservation model, to construct a new energy function processing multi-modal registration problem. We then applied the L-BFGS algorithm to optimize the energy function and solve complex three-dimensional data optimization problem. And finally we used the multi-scale hierarchical refinement ideas to solve large deformation registration. The experimental results showed that the proposed algorithm for large deformation and multi-modal three-dimensional medical image registration had good effects.
Objective To evaluate the quality of the registration information for trials sponsored by China registered in the WHO International Clinical Trial Registration Platform (ICTRP) primary registries or other registries that meet the requirements of the International Committee Medical Journal Editor (ICMJE). Methods We assessed the registration information for trials registered in the 9 WHO primary registries and one other registry that met the requirements of ICJME as of 15 October 2008. We analyzed the trial registration data set in each registry and assessed the registration quality against the WHO Trial Registration Data Set (TRDS). We also evaluated the quality of the information in the Source(s) of Monetary or Material Support section, using a specially prepared scale. Results The entries in four registries met the 20 items of the WHO TRDS. These were the Chinese Clinical Trial Registration Center (ChiCR), Australian New Zealand Clinical Trials Registry (NZCTR), Clinical Trials Registry – India (CTRI), and Sri Lanka Clinical Trials Registry (SLCTR). Registration quality varied among the different registries. For example, using the Scale of TRDS, the NZCTR scoreda median of 19 points, ChiCTR (median = 18 points), ISRCTN.org (median = 17 points), and Clinical trials.org (median = 12 points). The data on monetary or material support for ChiCTR and ISRCTN.org were relatively complete and the score on our Scale for the Completeness of Funding Registration Quality ranged from ChiCTR (median = 7 points), ISRCTN.org (median = 6 points), NZCTR (median = 3 points) to clinicaltrials.gov (median = 2 points). Conclusion Further improvements are needed in both the quantity and quality of trial registration. This could be achieved by full completion of the 20 items of the WHO TRDS. Future research should assess ways to ensure the quality and scope of research registration and the role of mandatory registration of funded research.
Based on previous evidence-based researches and teaching experience, our team conducted literature and book review, and summarized 4 requirements, 1) effect measure calculation and conversion, 2) registration of evidence-based research, 3) evidence-based research database and 4) quality evaluation tools and reporting guidelines. We developed an online platform of evidence-based medicine research helper using the front-end and back-end technology, which can be accessed using www.ebm-helper.cn. Currently, the online tool has included 46 scenarios for effect measure calculation and conversion, introduction of 7 evidence-based research registration platforms, 26 commonly used databases for evidence-based research and 29 quality evaluation tools and reporting guidelines. This online tool can help researchers to solve specific problems encountered in different stages of evidence-based medicine research. Promoting the application of this platform in evidence-based medicine will help researchers to use the tool scientifically and improve research efficiency.
In deep learning-based image registration, the deformable region with complex anatomical structures is an important factor affecting the accuracy of network registration. However, it is difficult for existing methods to pay attention to complex anatomical regions of images. At the same time, the receptive field of the convolutional neural network is limited by the size of its convolution kernel, and it is difficult to learn the relationship between the voxels with far spatial location, making it difficult to deal with the large region deformation problem. Aiming at the above two problems, this paper proposes a cascaded multi-level registration network model based on transformer, and equipped it with a difficult deformable region perceptron based on mean square error. The difficult deformation perceptron uses sliding window and floating window techniques to retrieve the registered images, obtain the difficult deformation coefficient of each voxel, and identify the regions with the worst registration effect. In this study, the cascaded multi-level registration network model adopts the difficult deformation perceptron for hierarchical connection, and the self-attention mechanism is used to extract global features in the basic registration network to optimize the registration results of different scales. The experimental results show that the method proposed in this paper can perform progressive registration of complex deformation regions, thereby optimizing the registration results of brain medical images, which has a good auxiliary effect on the clinical diagnosis of doctors.
In the process of positron emission tomography (PET) data acquiring, respiratory motion reduces the quality of PET imaging. In this paper, we present a correction method using three level grids B-spline elastic method to correct denoised and reorganized sinograms for respiratory motion correction. Using GATE simulates NCAT respiratory motion model to generate raw data which are used in experiment, the experiment results showed a significantly improved respiratory image with higher quality of PET, and the motion blur and structural information were fixed. The results proved the method of this paper would be effective for the elastic registration.
Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neuro-developmental disorders occurring in childhood, characterized by symptoms of age-inappropriate inattention, hyperactivity/impulsivity, and the prevalence is higher in boys. Although gray matter volume deficits have been frequently reported for ADHD children via structural magnetic resonance imaging, few of them had specifically focused on male patients. The present study aimed to explore the alterations of gray matter volumes in medicated-naive boys with ADHD via a relatively new voxel-based morphometry technique. According to the criteria of DSM-IV-TR, 43 medicated-naive ADHD boys and 44 age-matched healthy boys were recruited. The magnetic resonance image (MRI) scan was performed via a 3T MRI system with three-dimensional (3D) spoiled gradient recalled echo (SPGR) sequence. Voxel-based morphometry with diffeomorphic anatomical registration through exponentiated lie algebra in SPM8 was used to preprocess the 3D T1-weighted images. To identify gray matter volume differences between the ADHD and the controls, voxel-based analysis of whole brain gray matter volumes between two groups were done via two sample t-test in SPM8 with age as covariate, threshold at P＜0.001. Finally, compared to the controls, significantly reduced gray matter volumes were identified in the right orbitofrontal cortex (peak coordinates [-2,52,-25], t=4.01), and bilateral hippocampus (Left: peak coordinates [14,0,-18], t=3.61; Right: peak coordinates [-14,15,-28], t=3.64) of ADHD boys. Our results demonstrated obvious reduction of whole brain gray matter volumes in right orbitofrontal cortex and bilateral hippocampus in boys with ADHD. This suggests that the abnormalities of prefrontal-hippocam-pus circuit may be the underlying cause of the cognitive dysfunction and abnormal behavioral inhibition in medicated-naive boys with ADHD.
ObjectiveTo explore the function of information system platform in the management of outpatient registration source. MethodsOn the basis of registration appointment system, we surveyed again on outpatients traffic between February 6th and 10th in 2012 to find out find out the disadvantages of outpatient service procedures. Certain measures were taken for improvement, especially the management of registration source. ResultsAfter improvement by certain measures, queuing phenomenon and the degree of congestion in the waiting area were improved. To some extent, the satisfaction of patients and doctors was raised from 91% to 93%. ConclusionStandardizing outpatient administration and behavior of patients by information system platform has a good effect and is worth promoting.
ObjectivesTo analyze the development of acupuncture registered trials based on WHO international clinical trial registration platform (ICTRP) in the past 5 years.MethodsWHO ICTRP database was electronically searched to collect acupuncture-related clinical trials registered from January 1st, 2014 to December 31st, 2018. Two reviewers independently screened items, extracted data, and descriptive analysis was performed for the included trials.ResultsThe results showed that there were 1 556 registered clinical trials on acupuncture, and the most registered year was 2017. China was in the main country in applying for acupuncture-related clinical trials, however, the most registered unit was Kyung Hee University in Korea. The trials were mainly interventional research, mostly used randomized, blinded methods, and design modes were mainly based on parallel trials. In clinical trial phase, the majority were in the clinical trial period of treatment of new technologies. The field of clinical research was expected to be on pain in the future.ConclusionsAlthough acupuncture research is currently in a good stage of development, it should still value on the quality and innovative training of relevant trials, strengthen Chinese ties with other countries, focus on regional, domestic and international cooperation, expand research types, and enhance acupuncture applicability.