Craniofacial malformation caused by premature fusion of cranial suture of infants has a serious impact on their growth. The purpose of skull remodeling surgery for infants with craniosynostosis is to expand the skull and allow the brain to grow properly. There are no standardized treatments for skull remodeling surgery at the present, and the postoperative effect can be hardly assessed reasonably. Children with sagittal craniosynostosis were selected as the research objects. By analyzing the morphological characteristics of the patients, the point cloud registration of the skull distortion region with the ideal skull model was performed, and a plan of skull cutting and remodeling surgery was generated. A finite element model of the infant skull was used to predict the growth trend after remodeling surgery. Finally, an experimental study of surgery simulation was carried out with a child with a typical sagittal craniosynostosis. The evaluation results showed that the repositioning and stitching of bone plates effectively improved the morphology of the abnormal parts of the skull and had a normal growth trend. The child’s preoperative cephalic index was 65.31%, and became 71.50% after 9 months’ growth simulation. The simulation of the skull remodeling provides a reference for surgical plan design. The skull remodeling approach significantly improves postoperative effect, and it could be extended to the generation of cutting and remodeling plans and postoperative evaluations for treatment on other types of craniosynostosis.
Complete three-dimensional (3D) tooth model provides essential information to assist orthodontists for diagnosis and treatment planning. Currently, 3D tooth model is mainly obtained by segmentation and reconstruction from dental computed tomography (CT) images. However, the accuracy of 3D tooth model reconstructed from dental CT images is low and not applicable for invisalign design. And another serious problem also occurs,i.e. frequentative dental CT scan during different intervals of orthodontic treatment often leads to radiation to the patients. Hence, this paper proposed a method to reconstruct tooth model based on fusion of dental CT images and laser-scanned images. A complete 3D tooth model was reconstructed with the registration and fusion between the root reconstructed from dental CT images and the crown reconstructed from laser-scanned images. The crown of the complete 3D tooth model reconstructed with the proposed method has higher accuracy. Moreover, in order to reconstruct complete 3D tooth model of each orthodontic treatment interval, only one pre-treatment CT scan is needed and in the orthodontic treatment process only the laser-scan is required. Therefore, radiation to the patients can be reduced significantly.
Deformable image registration plays a crucial role in medical image analysis. Despite various advanced registration models having been proposed, achieving accurate and efficient deformable registration remains challenging. Leveraging the recent outstanding performance of Mamba in computer vision, we introduced a novel model called MCRDP-Net. MCRDP-Net adapted a dual-stream network architecture that combined Mamba blocks and convolutional blocks to simultaneously extract global and local information from fixed and moving images. In the decoding stage, we employed a pyramid network structure to obtain high-resolution deformation fields, achieving efficient and precise registration. The effectiveness of MCRDP-Net was validated on public brain registration datasets, OASIS and IXI. Experimental results demonstrated significant advantages of MCRDP-Net in medical image registration, with DSC, HD95, and ASD reaching 0.815, 8.123, and 0.521 on the OASIS dataset and 0.773, 7.786, and 0.871 on the IXI dataset. In summary, MCRDP-Net demonstrates superior performance in deformable image registration, proving its potential in medical image analysis. It effectively enhances the accuracy and efficiency of registration, providing strong support for subsequent medical research and applications.
By dividing the evolution of the U.S. clinical trial registration system into three phases—emergence, inception, and maturity—this study systematically traces its half-century development and reveals the underlying tensions and institutional logic. The U.S. clinical trial registration system is not merely a technical instrument, but a comprehensive institutional platform reconciling the conflicts among scientific rationality, commercial interests, and the public’s right to know. The emergence phase (1971—1985) originated from the establishment and public disclosure of the International Cancer Database to meet cancer research needs and safeguard patients’ survival rights. The inception phase (1986—2004) unfolded against the backdrop of the FDA’s drug approval crisis, with the construction of major disease registration systems breaking the regulatory deadlock and achieving an “incremental revolution”. The maturity phase (2004—2016) centered on controlling publication bias and advancing institutionalization and legalization. The 2004 paroxetine incident galvanized global consensus on trial registration, and the 2007 U.S. Congressional mandate marked the pivotal turning point toward a fully mature system. Today, China still faces low registration rates and insufficient legal constraints. Drawing on the U.S. experience, China should prioritize institutional publicness, legal enforceability, and the containment of publication bias to strategically upgrade its clinical trial registration system.
Neurosurgery navigation system, which is expensive and complicated to operate, has a low penetration rate, and is only found in some large medical institutions. In order to meet the needs of other small and medium-sized medical institutions for neurosurgical navigation systems, the scalp localization system of neurosurgery based on augmented reality (AR) theory was developed. AR technology is used to fuse virtual world images with real images. The system integrates computed tomography (CT) or magnetic resonance imaging (MRI) with the patient's head in real life to achieve the scalp positioning. This article focuses on the key points of Digital Imaging and Communications in Medicine (DICOM) standard, three-dimensional (3D) reconstruction, and AR image layer fusion in medical image visualization. This research shows that the system is suitable for a variety of mobile phones, can achieve two-dimensional (2D) image display, 3D rendering and clinical scalp positioning application, which has a certain significance for the auxiliary neurosurgical head surface positioning.
Objective To systematically evaluate the efficacy and safety of iris-registration in wavefront-guided LASIK (IR+WG LASIK) versus conventional LASIK for correction of myopia accompanied with astigmatism. Methods Such databases as PubMed, EMbase, The Cochrane library (Issue 2, 2012), CBM, CNKI, VIP, and WangFang Data were searched to collect the randomized controlled trials (RCTs) and quasi-RCTs about IR+WG LASIK versus conventional LASIK for correction of myopia accompanied with astigmatism. The retrieval time was from inception to February 2012, and the language was in both Chinese and English. Two reviewers independently screened the literature, extracted the data and assessed the quality of the included studies. Then the meta-analysis was performed by using RevMan 5.1 software. Results A total of 9 studies involving 3 903 eyes were included. The results of meta-analysis showed that, compared with the conventional LASIK group, the IR+WG LASIK group had a higher ratio in patients with postoperative uncorrected visual acuity no less than 1.0 (RR=1.03, 95%CI 1.01 to 1.05, P=0.002), as well as in patients with best-corrected visual acuity gained over 1 line (RR=1.75, 95%CI 1.49 to 2.16, Plt;0.000 01); it was smaller in the postoperative high order aberration RMS (WMD=−0.16, 95%CI −0.21 to −0.11, Plt;0.000 01), coma-like RMS (WMD=−0.05, 95%CI −0.11 to 0.00, P=0.07), spherical-like RMS (WMD=−0.15, 95%CI −0.23 to −0.07, P=0.000 2), and residual astigmatism (WMD=0.14, 95%CI 0.10 to 0.18, Plt;0.000 01); moreover, it was lower in the incidence of postoperative glare (RR=0.27, 95%CI 0.15 to 0.50, Plt;0.000 1), and it was higher in the subjective satisfaction of patients (RR=1.08, 95%CI 1.04 to 1.13, P=0.000 3). Conclusion Compared with conventional LASIK, IR+WG LASIK can more effectively reduce astigmatism, postoperative high order aberration RMS and spherical-like RMS. It can also get visual function including uncorrected visual acuity and best-corrected visual acuity, consequently increase patient’s satisfaction. But further studies are still required for its long-term effect.
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.
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.
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.