Mission-critical monitoring based on surround suppression variational Retinex enhancement for non-uniform illumination images

Abstract In this letter, a surround suppression variational Retinex enhancement algorithm (SSVR) is proposed for non-uniform illumination images. Instead of a gradient module, a surround suppression mechanism is used to provide spatial information in order to constrain the total variation regularization strength of the illumination and reflectance. The proposed strategy preserves the boundary areas in the illumination so that halo artifacts are prevented. It also preserves textural details in the reflectance to prevent from illumination compression, which further contributes to the contrast enhancement in the resulting image. In addition, strong regularization strength is enforced to eliminate uneven intensities in the homogeneous areas. The split Bregman optimization algorithm is employed to solve the proposed model. Finally, after decomposition, a contrast gain is added to reflectance for contrast enhancement, and a Laplacian-based gamma correction is added to illumination for prevent color cast. The recombination of the modified reflectance and illumination become the final result. Experimental results demonstrate that the proposed SSVR algorithm performs better than other methods

Multi-View Structural Local Subspace Tracking

In this paper, we propose a multi-view structural local subspace tracking algorithm based on sparse representation. We approximate the optimal state from three views: (1) the template view; (2) the PCA (principal component analysis) basis view; and (3) the target candidate view. Then we propose a unified objective function to integrate these three view problems together. The proposed model not only exploits the intrinsic relationship among target candidates and their local patches, but also takes advantages of both sparse representation and incremental subspace learning. The optimization problem can be well solved by the customized APG (accelerated proximal gradient) methods together with an iteration manner. Then, we propose an alignment-weighting average method to obtain the optimal state of the target. Furthermore, an occlusion detection strategy is proposed to accurately update the model. Both qualitative and quantitative evaluations demonstrate that our tracker outperforms the state-of-the-art trackers in a wide range of tracking scenarios

3D Printed Guides and Preoperative Planning for Uncemented Stem Anteversion Reconstruction during Hip Arthroplasty: A Pilot Study

Objective. To investigate if 3D printed guides and preoperative planning can accurately control femoral stem anteversion. Methods. A prospective comparative study was carried out from 2018 to 2020, including 53 patients who underwent hip arthroplasty for femoral neck fracture. The target rotation center of the femoral head is determined by three-dimensional planning. In group A, planning was made by 2D templates. In group B, preoperative 3D planning and 3D printed osteotomy/positioning guides were performed. After the operation, 3D model registration was performed to calculate the accuracy of anteversion restoration. Results. We screened 60 patients and randomized a total of 53 to 2 parallel study arms: 30 patients to the group A (traditional operation) and 23 patients to the group B (3D preoperative planning and 3D printed guide). There were no significant differences in demographic or perioperative data between study groups. The restoration accuracy of group A was 5.42°±3.65° and of group B was 2.32°±1.89°. The number and rate of abnormal cases was 15 (50%) and 2 (8.7%), respectively. Significant statistical differences were found in angle change, restoration accuracy, and number of abnormal cases. Conclusion. Three-dimensional preoperative planning and 3D printed guides can improve the accuracy of the restoration of femoral anteversion during hip arthroplasty

Non-uniform illumination endoscopic imaging enhancement via anti-degraded model and L 1 L 2-based variational retinex

Abstract In this paper, we propose a novel image enhancement algorithm via anti-degraded model and L 1 L 2-based variational retinex (AD-L 1 L 2VR) for non-uniform illumination endoscopic images. Firstly, a haze-free endoscopic image is obtained by an anti-degraded model named dark channel prior (DCP). For getting a more accurate transmission map, it is refined by using a guided image filtering. Secondly, the haze-free endoscopic image is decomposed into detail and naturalness components by light filtering. Thirdly, a logarithmic Laplacian-based gamma correction (LLGC) is added to the naturalness component for preventing color cast and uneven lighting. Fourthly, we assume that the error between the detail component of the haze-free image and the product of associated reflectance and background illumination follows Gaussian-Laplacian distribution. So, the associated reflectance component can be obtained by using the proposed L 1 L 2-based variational retinex (L 1 L 2VR) model. Finally, the recombination of modified naturalness component and associated reflectance component become the final result. Experimental results demonstrate that the proposed algorithm reveals more details in the background regions as well as other interesting areas and can mostly prevent the color cast. It has a better performance on increasing diagnosis and reducing misdiagnosis than other existing enhancement methods

Facile construction of calcium titanate-loaded silk fibroin scaffolds hybrid frameworks for accelerating neuronal cell growth in peripheral nerve regeneration

Different concentrations of calcium titanate (CaTiO3) nanoparticles were loaded into the Silk fibroin (SF) solution to construct porous SF@CaTiO3 hybrid scaffolds, which were shown to have enhanced properties for stimulating peripheral nerve regeneration. Surface charges, crystallization intensity, wettability, porosity, and morphology were measured and analyzed. We analyzed the hybrid porous SF@CaTiO3 scaffolds that affected the expansion of Schwann cells. The results demonstrated a concentration-dependent influence on the dispersion of nanoparticles in the CaTiO3 hybridized SF scaffolds. Incorporating CaTiO3-NPs into the porous SF@CaTiO3 hybrid scaffolds can boost hydrophobicity while decreasing surface charge density and porosity. The hybridized scaffolds mostly had an orthorhombic calcium titanate crystal structure with amorphous Silk fibroin mixed. Schwann cell cultures revealed that SF@CaTiO3 hybrid scaffolds containing an optimal CaTiO3-NPs concentration could stimulate the proliferation, attachment, and protection of Schwann cell biological functions, suggesting the scaffolds' potential for use in peripheral nerve regeneration