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This study aimed to investigate the correlation between the surface area ratio of medial tibial plateau (MTP) to lateral tibial plateau (LTP) and the mechanical tibiofemoral angle (mTFA).Lower limb computed tomography (CT) images were collected at our hospital. Then, the original CT data were analyzed and reconstructed using medical image processing software. The proximal and distal centres of the femur and tibia were marked. The surface areas of MTP and LTP were identified using image processing software. GraphPad Prism 8.0.2 was used to perform the statistical analysis.The surface area ratio of MTP to LTP was significantly correlated with the mTFA in all patients (P0.0001), male group (P0.0001), female group (P0.0001), varus group (P0.0001), and valgus group (P=0.002). Furthermore, the surface area of MTP and LTP was significantly greater in the male group than in the female group (P0.0001). There was significant difference in the surface area of the MTP between the varus and valgus groups (P0.0001). Significant difference was also observed in the surface area ratio of MTP to LTP between the varus and valgus groups (P0.0001).The surface area ratio of MTP to LTP was correlated with the mTFA. Within a certain range, the smaller the mTFA, the greater the surface area ratio of MTP to LTP. For patients undergoing total knee arthroplasty, of whom the surface area of the MTP was basically equal to that of the LTP, it is recommended that the osteotomy should be performed in accordance with mechanical alignment standards, and that a symmetrical tibial plateau prosthesis should be used. For patients whose surface area of MTP is significantly greater than that of the LTP, it is recommended that the osteotomy should be performed in accordance with kinematic alignment standards, and that an anatomical tibial plateau prosthesis should be used.

Since the end of 2019, coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide. The RNA genome of SARS-CoV-2, which is highly infectious and prone to rapid mutation, encodes both structural and nonstructural proteins. Vaccination is currently the only effective method to prevent COVID-19, and structural proteins are critical targets for vaccine development. Currently, many vaccines are in clinical trials or are already on the market. This review highlights ongoing advances in the design of prophylactic or therapeutic vaccines against COVID-19, including viral vector vaccines, DNA vaccines, RNA vaccines, live-attenuated vaccines, inactivated virus vaccines, recombinant protein vaccines and bionic nanoparticle vaccines. In addition to traditional inactivated virus vaccines, some novel vaccines based on viral vectors, nanoscience and synthetic biology also play important roles in combating COVID-19. However, many challenges persist in ongoing clinical trials.

Hydrophilic bone morphogenetic protein 2 (BMP2) is easily degraded and difficult to load onto hydrophobic carrier materials, which limits the application of polyester materials in bone tissue engineering. Based on soybean-lecithin as an adjuvant biosurfactant, we designed a novel cell-free-scaffold of polymer of poly(ε-caprolactone) and poly(lactide-co-glycolide)-co-polyetherimide with abundant entrapped and continuously released BMP2 for in vivo stem cell-capture and in situ osteogenic induction, avoiding the use of exogenous cells. The optimized bioactive osteo-polyester scaffold (BOPSC), i.e. SBMP-10SC, had a high BMP2 entrapment efficiency of 95.35%. Due to its higher porosity of 83.42%, higher water uptake ratio of 850%, and sustained BMP2 release with polymer degradation, BOPSCs were demonstrated to support excellent in vitro capture, proliferation, migration and osteogenic differentiation of mouse adipose derived mesenchymal stem cells (mADSCs), and performed much better than traditional BMP-10SCs with unmodified BMP2 and single polyester scaffolds (10SCs). Furthermore, in vivo capture and migration of stem cells and differentiation into osteoblasts was observed in mice implanted with BOPSCs without exogenous cells, which enabled allogeneic bone formation with a high bone mineral density and ratios of new bone volume to existing tissue volume after 6 months. The BOPSC is an advanced 3D cell-free platform with sustained BMP2 supply for in situ stem cell capture and osteoinduction in bone tissue engineering with potential for clinical translation., Graphical abstract Due to the introduction of soybean lecithin (SL) as a biosurfactant, bioactive osteo-polyester scaffold (BOPSC) loaded with BMP2 is a novel 3D cell-free-platform for in vitro/in vivo stem-cell capture and in-situ osteogenic induction. Optimized BOPSCs had a high BMP2 entrapment efficiency and perfect slow-release of activated BMP2, liking invisible hands, which can support excellent cell-capture, proliferation and osteogenic differentiation in mice without any exogenous cells.Image 1, Highlights • 3D Cell-Free-Platform for stem-cell capture and in situ osteogenic induction. • Soybean lecithin-mediated introduction of growth factors into polyesters. • No exogenous stem cells for bone regeneration.

Probe-based confocal laser endomicroscopy (pCLE) is a vital technology to realize in-vivo imaging of the organ surface in real-time. However, the field of view (FOV) of pCLE is too small to get a full picture of targeted tissues for diagnosing. It is recognized that collecting the image stream and assembling the images in a large mosaic can overcome FOV limitations. Many studies have been carried out to develop robust and fast methods for image processing to get a clear mosaic. However, it is still difficult to obtain high-quality images consistently due to the presence of tissue deformations on soft tissue surfaces. The control of probe movement is still a key research challenge. In this work, a position-based visual servoing scheme is proposed to achieve high accuracy and gap-less mosaics for soft tissue endomicroscopy. Experimental results show that the proposed control scheme with visual servoing can obtain a large and accurate spiral mosaic (approximately 7 mm 2) without gaps. Compared to open-loop control, the obtained trajectory better matches with the target one, with the error of circular trajectory reduced by 31.79% and the error of spiral trajectory reduced by 46.86% on average. The proposed control scheme has a high potential to achieve a large and accurate mosaic for soft tissue endomicroscopy.

Optical biopsy methods, such as probe-based endomicroscopy, can be used to identify early-stage gastric cancer in vivo. However, it is difficult to scan a large area of the gastric mucosa for mosaicking during endoscopy. In this work, we propose a miniaturised flexible instrument based on contact-aided compliant mechanisms and fibre Bragg grating (FBG) sensing for intraoperative gastric endomicroscopy. The instrument has a compact design with an outer diameter of 2.7 mm, incorporating a central channel with a diameter of 1.9 mm for the endomicroscopic probe to pass through. Experimental results show that the instrument can achieve raster trajectory scanning over a large tissue surface with a positioning accuracy of 0.5 mm. The tip force sensor provides a 4.6 mN resolution for the axial force and 2.8 mN for transverse forces. Validation with random samples shows that the force sensor can provide consistent and accurate three-axis force detection. Endomicroscopic imaging experiments were conducted, and the flexible instrument performed no gap scanning (mosaicking area more than 3 mm2) and contact force monitoring during scanning, demonstrating the potential of the system in clinical applications.

Purpose Cone-beam computed tomography (CBCT) is a common on-treatment imaging widely used in image-guided radiotherapy. Fast and accurate registration between the on-treatment CBCT and planning CT is significant for and precise adaptive radiotherapy treatment (ART). However, existing CT-CBCT registration methods, which are mostly affine or time-consuming intensity- based deformation registration, still need further study due to the considerable CT-CBCT intensity discrepancy and the artifacts in low-quality CBCT images. In this paper, we propose a deep learning-based CT-CBCT registration model to promote rapid and accurate CT-CBCT registration for radiotherapy. Methods The proposed CT-CBCT registration model consists of a registration network and an innovative deep similarity metric network. The registration network is a novel fully convolution network adapted specially for patch-wise CT-CBCT registration. The metric network, going beyond intensity, automatically evaluates the high-dimensional attribute-based dissimilarity between the registered CT and CBCT images. In addition, considering the artifacts in low-quality CBCT images, we add spatial weighting (SW) block to adaptively attach more importance to those informative voxels while inhibit the interference of artifact regions. Such SW-based metric network is expected to extract the most meaningful and discriminative deep features, and form a more reliable CT-CBCT similarity measure to train the registration network. Results We evaluate the proposed method on clinical thoracic CBCT and CT dataset, and compare the registration results with some other common image similarity metrics and some state-of-the-art registration algorithms. The proposed method provides the highest Structural Similarity index (86.17 ± 5.09), minimum Target Registration Error of landmarks (2.37 ± 0.32 mm), and the best DSC coefficient (78.71 ± 10.95) of tumor volumes. Moreover, our model also obtains comparable distance error of lung surfaces (1.75 ± 0.35 mm). Conclusion The proposed model shows both efficiency and efficacy for reliable thoracic CT-CBCT registration, and can generate the matched CT and CBCT images within few seconds, which is of great significance to clinical radiotherapy.

During flexible gastroscopy, physicians have extreme difficulties to self-localize. Camera tracking method such as simultaneous localization and mapping (SLAM) has become a research hotspot in recent years, allowing tracking of the endoscope. However, most of the existing solutions have focused on tasks in which sufficient texture information is available, such as laparoscope tracking, and cannot be applied to gastroscope tracking since gastroscopic images have fewer textures than laparoscopic images. This paper proposes a new monocular SLAM framework based on scale-invariant feature transform (SIFT) and narrow-band imaging (NBI), which extracts SIFT features instead of oriented features from accelerated segment test (FAST) and rotated binary robust independent elementary features (BRIEF) features from gastroscopic NBI images, and performs feature retention based on the response sorting strategy for achieving more matches. Experimental results show that the root mean squared error of the proposed algorithm can reach a minimum of 2.074 mm, and the pose accuracy can be improved by up to 25.73% compared with oriented FAST and rotated BRIEF (ORB)-SLAM. SIFT features and response sorting strategy can achieve more accurate matching in gastroscopic NBI images than other features and homogenization strategy, and the proposed algorithm can also run successfully on real clinical gastroscopic data. The proposed algorithm has the potential clinical value to assist physicians in locating the gastroscope during gastroscopy.

BackgroundThe problem of visualizing a hierarchical dataset is an important and useful technique in many real-life situations. Folder systems, stock markets, and other hierarchical-related datasets can use this technique to better understand the structure and dynamic variation of the dataset. Traditional space-filling(square)-based methods have the advantages of compact space usage and node size as opposed to diagram-based methods. Spacefilling- based methods have two main research directions: static and dynamic performance.MethodsThis study presented a treemapping method based on balanced partitioning that enables excellent aspect ratios in one variant, good temporal coherence for dynamic data in another, and in the third, a satisfactory compromise between these two aspects. To layout a treemap, all the children of a node were divided into two groups, which were then further divided until groups of single elements were reached. After this, these groups were combined to form a rectangle representing the parent node. This process was performed for each layer of the hierarchical dataset. For the first variant from the partitioning, the child elements were sorted and two groups, sized as equally as possible, were built from both big and small elements (size-balanced partition). This achieved satisfactory aspect ratios for the rectangles but less so temporal coherence (dynamic). For the second variant, the sequence of children was taken and from this, groups, sized as equally as possible, were created without the need for sorting (sequence-based, good compromise between aspect ratio and temporal coherency). For the third variant, the children were split into two groups of equal cardinalities, regardless of their size (number-balanced, worse aspect ratios but good temporal coherence).ResultsThis study evaluated the aspect ratios and dynamic stability of the employed methods and proposed a new metric that measures the visual difference between rectangles during their movement to represent temporally changing inputs.ConclusionThis study demonstrated that the proposed method of treemapping via balanced partitioning outperformed the state-of-the-art methods for several real-world datasets. published

Image mosaicking has emerged as a universal technique to broaden the field-of-view of the probe-based confocal laser endomicroscopy (pCLE) imaging system. However, due to the influence of probe-tissue contact forces and optical components on imaging quality, existing mosaicking methods remain insufficient to deal with practical challenges. In this paper, we present the texture encoded sum of conditional variance (TESCV) as a novel similarity metric, and effectively incorporate it into a sequential mosaicking scheme to simultaneously correct rigid probe shift and nonrigid tissue deformation. TESCV combines both intensity dependency and texture relevance to quantify the differences between pCLE image frames, where a discriminative binary descriptor named fully cross-detected local derivative pattern (FCLDP) is designed to extract more detailed structural textures. Furthermore, we also analytically derive the closed-form gradient of TESCV with respect to the transformation variables. Experiments on the circular dataset highlighted the advantage of the TESCV metric in improving mosaicking performance compared with the other four recently published metrics. The comparison with the other four state-of-the-art mosaicking methods on the spiral and manual datasets indicated that the proposed TESCV-based method not only worked stably at different contact forces, but was also suitable for both low- and high-resolution imaging systems. With more accurate and delicate mosaics, the proposed method holds promises to meet clinical demands for intraoperative optical biopsy.

Collagen is a kind of biocompatible protein material, which is widely used in medical tissue engineering, drug delivery, cosmetics, food and other fields. Because of its wide source, low extraction cost and good physical and chemical properties, it has attracted the attention of many researchers in recent years. However, the application of collagen derived from terrestrial organisms is limited due to the existence of diseases, religious beliefs and other problems. Therefore, exploring a wider range of sources of collagen has become one of the main topics for researchers. Marine-derived collagen (MDC) stands out because it comes from a variety of sources and avoids issues such as religion. On the one hand, this paper summarized the sources, extraction methods and characteristics of MDC, and on the other hand, it summarized the application of MDC in the above fields. And on the basis of the review, we found that MDC can not only be extracted from marine organisms, but also from the wastes of some marine organisms, such as fish scales. This makes further use of seafood resources and increases the application prospect of MDC.

Due to the limited field of view (FOV), the probe-based confocal laser endomicroscopy (pCLE) imaging system remains challenging to be widely used in clinic. Existing video mosaicking approaches are usually troubled by poor real-time capability and sensitivity to tissue deformations and intensity fluctuations. In this paper, a novel pCLE mosaicking algorithm that simultaneously implements rigid probe motion tracking and inter-frame tissue deformation correction is proposed. The sum of conditional variance (SCV) metric with low calculational complexity and intensity variation invariance is embedded into the reconstruction of pCLE mosaics. We also deduce the derivatives of the SCV metric with respect to transformation variables to enhance the robustness of numerical solutions. Moreover, a parallel acceleration mechanism that maximally exploits the resources of graphics processing unit (GPU) is designed to boost mosaicking efficiency. Experiments on lens tissue paper and swine tissue highlight the excellent mosaicking accuracy of the proposed method in this field. It is also verified that the mosaic-king rate of the proposed method exceeds 14 frames per second (fps), which can keep up with the acquisition rate of most pCLE imaging systems (8 fps~12 fps). Benefiting from finer mosaics and faster speed, the proposed algorithm has high potential to achieve large and accurate mosaicking for intraoperative endomicroscopy.

Probe-based confocal laser endomicroscopy (pCLE) is a promising imaging tool that provides in situ and in vivo optical imaging to perform real-time pathological assessments. However, due to limited field of view, it is difficult for clinicians to get a full understanding of the scanned tissues. In this paper, we develop a novel mosaicing framework to assemble all frame sequences into a full view image. First, a hybrid rigid registration that combines feature matching and template matching is presented to achieve a global alignment of all frames. Then, the parametric free-form deformation (FFD) model with a multiresolution architecture is implemented to accommodate non-rigid tissue distortions. More importantly, we devise a robust similarity metric called context-weighted correlation ratio (CWCR) to promote registration accuracy, where spatial and geometric contexts are incorporated into the estimation of functional intensity dependence. Experiments on both robotic setup and manual manipulation have demonstrated that the proposed scheme significantly precedes some state-of-the-art mosaicing schemes in the presence of intensity fluctuations, insufficient overlap and tissue distortions. Moreover, the comparisons of the proposed CWCR metric and two other metrics have validated the effectiveness of the context-weighted strategy in quantifying the differences between two frames. Benefiting from more rational and delicate mosaics, the proposed scheme is more suitable to instruct diagnosis and treatment during optical biopsies.

In contrast to the early acting bone morphogenetic protein 2, bone morphogenetic protein 7 (BMP7) plays a decisive role mainly in the late stages of bone formation. To overcome deactivation and degradation of expensive BMP7, we designed a novel long-acting BMP7 release system based on poly(3-hydroxybutyrate-co-4-hydroxybutyrate) (P34HB) nanoparticles to enable the induction of osteogenic differentiation in human adipose mesenchymal stem cells (ADSCs). In order to improve the encapsulation efficiency of BMP7 and avoid damage by organic solvents, BMP7 was modified and protected using the biosurfactant soybean lecithin. In an in vitro test, BMP7-soybean lecithin-P34HB nanoparticles (BMP7-SPNPs) showed a short initial burst of BMP7 release during the first 24h, followed by a steady increase to a cumulative 80% release in 20days. Compared with the rapid release of control P34HB nanoparticles without soybean phospholipids loaded with BMP7 without soybean lecithin, BMP7-SPNPs significantly reduced the initial burst of BMP7 release and stabilized the content of BMP7 to allow long-term osteogenic differentiation during the late phase of bone development. Human ADSCs treated with BMP7-SPNPs showed higher alkaline phosphatase activity and higher expression levels of genetic markers of osteogenic differentiation compared with the control group. Thus, the results indicate that BMP7-SPNPs can be used as a rapid and long-acting BMP7 delivery system for osteogenic differentiation.

The computed tomography (CT) imaging technique has been used to diagnose widespread disease for many years; however, severe streaking artifacts have been observed to appear in the reconstructed images of examinate contains metal objects. In this paper, we propose a dynamic wavelet thresholding metal artifact reduction (MAR) algorithm based on a statistic iterative reconstruction (SIR) model for 2-D fan beam CT. Cubic spline interpolation is utilized to remove blocky black artifacts caused by incomplete projections, and it also makes the solution closer to the optimum. The dynamic wavelet thresholding method contains the benefits of both wavelet soft and hard thresholding methods and promotes the sparsity of the image, which is used to erase residual streaking artifacts and accelerate the convergence of the SIR. The algorithm is accelerated by graphics processing unit programming and costs 14.44s with 40 iterations, meeting the demand of clinical practice. The performance of the proposed algorithm is compared with two classical MAR algorithms: the total variation (TV) constraint SIR algorithm and the reweighted TV constraint SIR algorithm. The experimental datasets include nine artificial datasets. Both qualitative and quantitative evaluation results show the outstanding performance of the proposed algorithm in suppressing the metal artifacts and preserving the image details.

In firefighting area, the novel CH 3 N 5 -Sr(NO 3 ) 2 is of growing interest as solid propellant gas generating agent. However, undesirable reaction temperature and burning rate of CH 3 N 5 -Sr(NO 3 ) 2 limit their applications to fire-fighting systems, which forces fire researchers to find more fitting ingredient proportions or burning rate catalysts. This paper presents a detailed experimental study adding nanosized metal oxides (Fe 2 O 3 , CuO, and NiO) effects on CH 3 N 5 -Sr(NO 3 ) 2 burning behaviors, including thermal analysis, scanning electron microscopy, specific surface area measurement, and thermal conductivity test. Results show, the additions of transition metal oxides (TMOs) increase the burning rate of the CH 3 N 5 -Sr(NO 3 ) 2 -based propellants and decrease reaction temperature. The modifying effects of TMOs on combustion behavior alter both the condensed phase and gas phase reactions in a synergistic manner. The novel propellant formulation has shown a superior property to promote CH 3 N 5 -Sr(NO 3 ) 2 -based propellants’ application into fire-fighting area.

The 5AT/Sr(NO3)2 mixture has recently attracted attention as a gas-generating agent for use in novel fire-suppression applications. However, it cannot provide the desired combustion behavior alone. Thus, nitroguanidine (NQ) was added as a fuel component to 5AT/Sr(NO3)2 in attempt to improve the mixture's combustion behavior. The effects of NQ on the thermal and burning characteristics of 5AT/Sr(NO3)2 were investigated. Thermogravimetry-differential scanning calorimetric (TG-DSC) analysis with four heating rates (5, 10, 15, 20 K min−1) under a nitrogen atmosphere was performed to determine the thermal characteristics and non-isothermal reaction kinetic parameters. The addition of NQ decreases the activation energy of the Stage II and III decomposition reaction, and accelerates the redox reaction and decomposition of Sr(NO3)2. Thermodynamic calculations and measurements of temperature profile and liner burning rates were performed to evaluate the combustion characteristics. Adding NQ decreased the adiabatic combustion temperature, outlet temperature, average flame height, flame oscillation frequency and pressure exponent of Vieille's equation, and increased the gas output and linear burning rate. Notably, mesa burning occurred when NQ was added, the mechanism of which is elaborated using a physical combustion model. The analysis deepens the understanding of when the gas-phase or condensed-phase reactions control the burning characteristics of the composite propellant.

The article relies on the Guang-Xing section of the southern section of the third phase of Chengdu Metro Line 1 to cross the Cheng-Hua Railway. The change of the stress with the approaching is analyzed. Study the stress change law of the intercalated rock under the change of the distance and angle: when the distance decreases, the maximum principal stress increases more obviously, which shows that the smaller distance, the easier the damage of intercalated rock. The stress state of the rock at different angles is that it is safer to overpassing and undercrossing, the horizontal approach is the most dangerous, and the other angles tend to be between the two. Through three-dimensional numerical simulation, the influence of the excavation process and construction method is analyzed, and it is found that the change of the secondary stress on the sandwiched rock by the mining method is relatively larger than that of the shield method. This makes the surrounding rock disturbance relatively large, resulting in the weakening of the sandwiched rock, which is directly manifested as the increase of the subgrade displacement.

The effects of CaCO 3 on thermal and combustion characteristics of solid propellants composed of the novel green energetic material 5AT/Sr(NO 3 ) 2 are examined. Thermogravimetry–derivative thermogravimetry (TG–DTG), thermocouple measurements and closed bomb calorimetry are all employed to study the reaction mechanisms obtained when using CaCO 3 as a cooling additive. In this manner, the combustion temperatures, burning rates, pressure exponents, thermal behaviors and non-isothermal reaction kinetics of solid propellant specimens are assessed. The combustion of the 5AT/Sr(NO 3 ) 2 propellant with added CaCO 3 can be divided into two regions. The initial region is dominated by condensed phase reactions and exhibits a lower decomposition temperature, lower activation energy and higher burning rate. These results demonstrate that the addition of CaCO 3 increases the reactivity of the propellant. The latter region is primarily associated with gas phase reactions, and the decomposition temperature and activation energy all appear to be elevated in this region, although the exhaust gas temperature and burning rate are greatly reduced. The pressure exponent is also reduced significantly in this stage, providing evidence for increased combustion stability. The thermal characteristics of the decomposition reaction as observed microscopically indicate significant synergistic effects of the CaCO 3 on the burning behavior. CaCO 3 addition has been shown to generate a significant cooling effect and the combination of this compound with 5AT/Sr(NO 3 ) 2 results in a propellant with excellent thermal behavior and steady combustion. This propellant formulation is safe, scalable and inexpensive and therefore CaCO 3 appears to be an ideal agent for the modification of the gas generation performance of solid propellants.

Crack is one of the most common lining deteriorations, which is generally regarded as an indicator of tunnel safety. The present study investigated the lining cracks of 11 tunnels which are 200 km away from the Longmenshan fault zone. In order to evaluate the seismic capacity of these tunnels with longitudinal cracks in the permanent lining, a modified deformation-based pseudo-static assessment method was developed. The propagation of lining cracks was simulated by a reconstructed damaged plasticity constitutive model of reinforced concrete. The analyses adopted a two-dimensional finite element model and took tunnel depth, initial crack position, and the interaction between soil and lining structures into account. The analysis results showed that the modified evaluation method could simulate the damage process of lining structures under the action of seismic shear wave well. The results also showed that the failure modes of tunnels with cracked permanent lining were different with different burial depth in an earthquake. The cracks in the spandrel had the greatest impact on the seismic capacity of tunnels and should be reinforced in time before the earthquake. In addition, the interaction between the temporary support and permanent lining had little effect on the damage process of linings but had an impact on the damage speed. This study can provide a reference for the safety assessment of cracked lining tunnels in seismically active areas and help to determine the reinforcement measures and time more reasonably.

In order to analyse the safety of the two main line tunnels and two ramp tunnels crossing the existing Bajiaogou tunnel in Chongqing University City, the plane and three-dimensional models were established to study the impact on the existing railway tunnels by strength reduction method and structure analysis method. Research results: the influence of different excavation bench lengths (6m and 12m) on the existing tunnel is analysed, and suitable excavation bench length is 6m. According to the deformation rule of the lining rigid body structure, the displacement control value of the C35 lining structure is 5.9mm. Various excavation procedures have different effects on the structure and the overall stability of the surrounding rock, so optimizing the excavation process can reduce the impact of construction. Optimization principles are derived from the structural displacement time history curve of the optimal conditions. The principles: interval excavation of approaching large-section tunnels, avoiding multiple disturbances in a short time, excavating the distant tunnel before the vicinity and excavating the upper tunnel before the below. The conclusions have guiding significance for the optimization of the four large-section tunnels’ approaching construction.

To establish the flexural performance of a retrofitted anchor-bolted steel plate reinforced structure as a cast-in-place tunnel lining, we conducted a numerical analysis using bend-compression tests. The current rehabilitation structure involves the combination of a long bolt and an H-shaped steel girder. However, installing the long bolt is complex and can damage the waterproof structure. Furthermore, the H-shaped steel girder can intrude into the tunnel clearance. To overcome these limitations, we replaced the existing long bolts and H-shaped steel girder structure with girders using short bolts. The developed numerical model was validated against the experiment model based on the failure pattern, load-deflection, and load-strain results. Three initialised cracks of different depths were considered and produced on the beams. The numerical results unveiled the flexural-tensile failure pattern and demonstrated significant enhancements in flexural capacity, stiffness, and ductility. The proposed short anchor-bolted steel plate system is a viable option for repairing cast-in-place tunnel linings.

Non-rigid multi-modal image registration plays an important role in many medical applications. Many advanced methods have been developed in deformable registration. However, conventional non-rigid registration assumes a global smooth deformation field throughout the image, so difficulties arise with handling the discontinuous displacement field and lead to poor correspondences at these sliding boundaries. These discontinuities exist for organs such as liver or lungs, which have a sliding motion during respiration. In this chapter we use total variation (TV) as a term to preserve the discontinuous boundaries for liver registration on computed tomography (CT)/magnetic resonance imaging. With benefits from the parametric transformation model known as free-form deformation, we analytically acquire an explicit optimization scheme for our method and compare our method with L2 regularization on both public and clinical data sets. The proposed method has been demonstrated to have a more credible displacement field near the discontinuous interface in both the public 4-dimensional CT data set and the clinical CT/magnetic resonance imaging data set.

Objective: Nonrigid image registration with high accuracy and efficiency remains a challenging task for medical image analysis. In this paper, we present the spatially region-weighted correlation ratio (SRWCR) as a novel similarity measure to improve the registration performance. Methods: SRWCR is rigorously deduced from a three-dimension joint probability density function combining the intensity channels with an extra spatial information channel. SRWCR estimates the optimal functional dependence between the intensities for each spatial bin, in which the spatial distribution modeled by a cubic B-spline function is used to differentiate the contribution of voxels. We also analytically derive the gradient of SRWCR with respect to the transformation parameters and optimize it using a quasi-Newton approach. Furthermore, we propose a GPU-based parallel mechanism to accelerate the computation of SRWCR and its derivatives. Results: The experiments on synthetic images, public four-dimensional thoracic computed tomography (CT) dataset, retinal optical coherence tomography data, and clinical CT and positron emission tomography images confirm that SRWCR significantly outperforms some state-of-the-art techniques such as spatially encoded mutual information and Robust PaTch-based cOrrelation Ration. Conclusion: This study demonstrates the advantages of SRWCR in tackling the practical difficulties due to distinct intensity changes, serious speckle noise, or different imaging modalities. Significance: The proposed registration framework might be more reliable to correct the nonrigid deformations and more potential for clinical applications.

Background To improve the accuracy of ultrasound-guided biopsy of the prostate, the non-rigid registration of magnetic resonance (MR) images onto transrectal ultrasound (TRUS) images has gained increasing attention. Mutual information (MI) is a widely used similarity criterion in MR-TRUS image registration. However, the use of MI has been challenged because of intensity distortion, noise and down-sampling. Hence, we need to improve the MI measure to get better registration effect. Methods We present a novel two-dimensional non-rigid MR-TRUS registration algorithm that uses correlation ratio-based mutual information (CRMI) as the similarity criterion. CRMI includes a functional mapping of intensity values on the basis of a generalized version of intensity class correspondence. We also analytically acquire the derivative of CRMI with respect to deformation parameters. Furthermore, we propose an improved stochastic gradient descent (ISGD) optimization method based on the Metropolis acceptance criteria to improve the global optimization ability and decrease the registration time. Results The performance of the proposed method is tested on synthetic images and 12 pairs of clinical prostate TRUS and MR images. By comparing label map registration frame (LMRF) and conditional mutual information (CMI), the proposed algorithm has a significant improvement in the average values of Hausdorff distance and target registration error. Although the average Dice Similarity coefficient is not significantly better than CMI, it still has a crucial increase over LMRF. The average computation time consumed by the proposed method is similar to LMRF, which is 16 times less than CMI. Conclusion With more accurate matching performance and lower sensitivity to noise and down-sampling, the proposed algorithm of minimizing CRMI by ISGD is more robust and has the potential for use in aligning TRUS and MR images for needle biopsy.

Background and objective Deformable registration is very significant for various clinical image applications. Unfortunately, existing conventional medical image registration approaches, which involve time-consuming iterative optimization, have not reached the level of routine clinical practice in terms of registration time and robustness. The aim of this study is to propose a tuning-free 3D image registration model based on adversarial deep network, and to achieve rapid and high-accurate registration. Methods We propose a fully convolutional network (FCN) to regress the 3D dense deformation field in one shot from the to-be-registered image pair. To precisely regress the complex deformation and produce optimal registration, we design the FCN as a novel multi-scale frame to capture the complementary multi-scale image features and effectively characterize the spatial correspondence between the image pair. Moreover, we learn a discriminator network simultaneously to discriminate the registered two images, where the discrimination loss helps further update the FCN. Thus by the adversarial training strategy, the registration network is urged to produce well-registered two images that are indistinguishable for the discriminator. Results We perform registration experiments on four different brain MR datasets using the model trained by ANDI database. Compared with some state-of-the-art registration algorithms including other newest deeplearning-based methods, the proposed method provides a considerable increase of large than 4% in terms of Dice similarity coefficient (DSC). Moreover, our model also obtains comparable distance errors. More significantly, our model can achieve a high-accurate 3D registration result in average 0.74 s, with roughly hundred speed-up over conventional registration methods. Conclusions The proposed model shows consistent high performance for various registration tasks under a second without any additional parameter tuning, which proves its potential for real-time clinical applications.