Morphological Reconstruction for Variable Wing Leading Edge Based on the Node Curvature Vectors

Precise morphology acquisition for the variable wing leading edge is essential for its bio-inspired adaptive control. Therefore, this study proposes a morphological reconstruction method for the variable wing leading edge, utilizing the node curvature vectors-based curvature propagation method (NCV-CPM). By establishing a strain-arc curvature function, the method fundamentally mitigates the impact of surface curvature angle on curvature computation accuracy at sensing points. We introduce a technique that uses high-order curvature fitting functions to determine the curvature vectors of arc segment nodes. This method reduces cumulative errors in curvature computation linked to the linear interpolation-based curvature propagation method (LI-CPM) at unattached sensor positions. Integrating curvature-strain functions aids in wing leading-edge strain field reconstruction, supporting structural health monitoring. Additionally, a particle swarm algorithm optimizes the sensing point distribution, reducing network complexity. This study demonstrates significantly enhanced morphological reconstruction accuracy compared to those obtained with conventional LI-CPM.

Near-Field Terahertz Morphological Reconstruction Nanoscopy for Subsurface Imaging of Protein Layers

Protein layers formed on solid surfaces have important applications in various fields. High-resolution characterization of the morphological structures of protein forms in the process of developing protein layers has significant implications for the control of the layer's quality as well as for the evaluation of the layer's performance. However, it remains challenging to precisely characterize all possible morphological structures of protein in various forms, including individuals, networks, and layers involved in the formation of protein layers with currently available methods. Here, we report a terahertz (THz) morphological reconstruction nanoscopy (THz-MRN), which can reveal the nanoscale three-dimensional structural information on a protein sample from its THz near-field image by exploiting an extended finite dipole model for a thin sample. THz-MRN allows for both surface imaging and subsurface imaging with a vertical resolution of ∼0.5 nm, enabling the characterization of various forms of proteins at the single-molecule level. We demonstrate the imaging and morphological reconstruction of single immunoglobulin G (IgG) molecules, their networks, a monolayer, and a heterogeneous double layer comprising an IgG monolayer and a horseradish peroxidase-conjugated anti-IgG layer. The established THz-MRN presents a useful approach for the label-free and nondestructive study of the formation of protein layers.

Morphological Reconstruction of a Critical-Sized Bone Defect in the Maxillofacial Region Using Modified Chitosan in Rats with Sub-Compensated Type I Diabetes Mellitus

It is known that complexes based on natural polysaccharides are able to eliminate bone defects. Prolonged hyperglycemia leads to low bone regeneration and a chronic inflammatory response. The purpose of this study was to increase the efficiency of early bone formation in a cavity of critical size in diabetes mellitus in the experiment. The polyelectrolyte complex contains high-molecular ascorbate of chitosan, chondroitin sulfate, sodium hyaluronate, heparin, adgelon serum growth factor, sodium alginate and amorphous nanohydroxyapatite (CH-SA-HA). Studies were conducted on five groups of white female Wistar rats: group 1-regeneration of a bone defect in healthy animals under a blood clot; group 2-regeneration of a bone defect under a blood clot in animals with diabetes mellitus; group 3-bone regeneration in animals with diabetes mellitus after filling the bone cavity with a collagen sponge; group 4-filling of a bone defect with a CH-SA-HA construct in healthy animals; group 5-filling of a bone defect with a CH-SA-HA construct in animals with diabetes mellitus. Implantation of the CH-SA-HA construct into bone cavities in type I diabetic rats can accelerate the rate of bone tissue repair. The inclusion of modifying polysaccharides and apatite agents in the construction may be a prospect for further improvement of the properties of implants.

A Multiscale Method for Infrared Ship Detection Based on Morphological Reconstruction and Two-Branch Compensation Strategy

Infrared ship target detection is crucial technology in marine scenarios. Ship targets vary in scale throughout navigation because the distance between the ship and the infrared camera is constantly changing. Furthermore, complex backgrounds, such as sea clutter, can cause significant interference during detection tasks. In this paper, multiscale morphological reconstruction-based saliency mapping, combined with a two-branch compensation strategy (MMRSM-TBC) algorithm, is proposed for the detection of ship targets of various sizes and against complex backgrounds. First, a multiscale morphological reconstruction method is proposed to enhance the ship targets in the infrared image and suppress any irrelevant background. Then, by introducing a structure tensor with two feature-based filter templates, we utilize the contour information of the ship targets and further improve their intensities in the saliency map. After that, a two-branch compensation strategy is proposed, due to the uneven distribution of image grayscale. Finally, the target is extracted using an adaptive threshold. The experimental results fully show that our proposed algorithm achieves strong performance in the detection of different-sized ship targets and has a higher accuracy than other existing methods.

Laminar and dorsoventral organization of layer 1 interneuronal microcircuitry in superficial layers of the medial entorhinal cortex

Layer 1 (L1) interneurons (INs) participate in various brain functions by gating information flow in the neocortex, but their role in the medial entorhinal cortex (MEC) is still unknown, largely due to scant knowledge of MEC L1 microcircuitry. Using simultaneous triple-octuple whole-cell recordings and morphological reconstructions, we comprehensively depict L1IN networks in the MEC. We identify three morphologically distinct types of L1INs with characteristic electrophysiological properties. We dissect intra- and inter-laminar cell-type-specific microcircuits of L1INs, showing connectivity patterns different from those in the neocortex. Remarkably, motif analysis reveals transitive and clustered features of L1 networks, as well as over-represented trans-laminar motifs. Finally, we demonstrate the dorsoventral gradient of L1IN microcircuits, with dorsal L1 neurogliaform cells receiving fewer intra-laminar inputs but exerting more inhibition on L2 principal neurons. These results thus present a more comprehensive picture of L1IN microcircuitry, which is indispensable for deciphering the function of L1INs in the MEC.

The area-reconstruction h-dome technique and its efficient Python implementation for improved particle size image analysis

The traditional watershed segmentation methods usually suffer from over segmentation for irregularly shaped particles. This is because the distance map of an irregularly shaped particle contains multiple local maxima, and over segmentation would happen if these local maxima were used as seeds for watershed segmentation. In this work, several methods based on morphological reconstruction, including h-dome transform, h-maxima, and area-reconstruction h-dome transform, are introduced to merge, or erase redundant local maxima, and the performance of these methods in avoiding over segmentation is compared. The results show that the area-reconstruction h-dome transform is the most effective method in controlling over segmentation among the evaluated methods. However, the area-reconstruction h-dome transform is achieved by superposition of binary reconstructions at each grayscale level, which is extremely time-consuming and impractical for batch processing. A hybrid pixel-queue algorithm is applied to accelerate the area-reconstruction h-dome transform, and the algorithm is implemented in Cython to further improve the computational efficiency. For a 2592 × 1944 pixel image, on a PC with an Intel Core i5 2.4GHz processor and 8 GB RAM, the processing time of the area-reconstruction h-dome transform after acceleration is about 549 ms, which is 249 times faster than the unaccelerated algorithm and 4 times faster than the reconstruction function in the Scikit-image library (an open-source image processing library for the Python programming language) which performs reconstruction by dilation. The accelerated area-reconstruction h-dome transform algorithm was successfully applied to the segmentation of rubber particles in a thermoplastic polyolefin (TPO) compound. RESEARCH HIGHLIGHTS: Techniques for segmenting particles with irregular shapes based on morphological reconstruction are reviewed. A fast algorithm for area-reconstruction h-dome transform is introduced based on Vincent's first approach combined with the pixel queue algorithm and Cython acceleration. The accelerated reconstruction algorithm is 249 times faster than the unaccelerated algorithm. The fast area-reconstruction h-dome transform algorithm is successfully applied to rubber particle segmentation of a thermal plastic polyolefin.

Hyperreflective Foci Enhancement in a Combined Spatial-Transform Domain for SD-OCT Images

Purpose

Spectral-domain optical coherent tomography (SD-OCT) is a useful tool for visualizing, treating, and monitoring retinal abnormality in patients with different retinal diseases. However, the assessment of SD-OCT images is thwarted by the lack of image quality necessary for ophthalmologists to analyze and quantify the diseases. This has hindered the potential role of hyperreflective foci (HRF) as a prognostic indicator of visual outcome in patients with retinal diseases. We present a new multi-vendor algorithm that is robust to noise while enhancing the HRF in SD-OCT images.

Methods

The proposed algorithm processes the SD-OCT images in two parallel processes simultaneously. The two parallel processes are combined by histogram matching. An inverse of both logarithmic and orthogonal transforms is applied to the mapped data to produce the enhanced image.

Results

We evaluated our algorithm on a dataset composed of 40 SD-OCT volumes. The proposed method obtained high values for the measure of enhancement, peak signal-to-noise ratio, structure similarity, and correlation (ρ) and a low value for mean square error of 36.72, 38.87, 0.87, 0.98, and 25.12 for Cirrus; 40.77, 41.84, 0.89, 0.98, and 22.15 for Spectralis; and 30.81, 32.10, 0.81, 0.96, and 28.55 for Topcon SD-OCT devices, respectively.

Conclusions

The proposed algorithm can be used in the medical field to assist ophthalmologists and in the preprocessing of medical images.

Translational Relevance

The proposed enhancement algorithm facilitates the visualization and detection of HRF, which is a step forward in assisting clinicians with decision making about patient treatment planning and disease monitoring.

Region growing algorithm combined with morphology and skeleton analysis for segmenting airway tree in CT images

BACKGROUND

Automatic segmentation of pulmonary airway tree is a challenging task in many clinical applications, including developing computer-aided detection and diagnosis schemes of lung diseases.

OBJECTIVE

To segment the pulmonary airway tree from the computed tomography (CT) chest images using a novel automatic method proposed in this study.

METHODS

This method combines a two-pass region growing algorithm with gray-scale morphological reconstruction and leakage elimination. The first-pass region growing is implemented to obtain a rough airway tree. The second-pass region growing and gray-scale morphological reconstruction are used to detect the distal airways. Finally, leakage detection is performed to remove leakage and refine the airway tree.

RESULTS

Our methods were compared with the gold standards. Forty-five clinical CT lung image scan cases were used in the experiments. Statistics on tree division order, branch number, and airway length were adopted for evaluation. The proposed method detected up to 12 generations of bronchi. On average, 148.85 branches were extracted with a false positive rate of 0.75%.

CONCLUSIONS

The results show that our method is accurate for pulmonary airway tree segmentation. The strategy of separating the leakage detection from the segmenting process is feasible and promising for ensuring a high branch detected rate with a low leakage volume.

Dendritic Arborization Patterns of Small Juxtaglomerular Cell Subtypes within the Rodent Olfactory Bulb

Within the glomerular layer of the rodent olfactory bulb, numerous subtypes of local interneurons contribute to early processing of incoming sensory information. Here we have investigated dopaminergic and other small local juxtaglomerular cells in rats and mice and characterized their dendritic arborization pattern with respect to individual glomeruli by fluorescent labeling via patching and reconstruction of dendrites and glomerular contours from two-photon imaging data. Dopaminergic neurons were identified in a transgenic mouse line where the expression of dopamine transporter (DAT) was labeled with GFP. Among the DAT+ cells we found a small short-axon cell (SAC) subtype featuring hitherto undescribed dendritic specializations. These densely ramifying structures clasped mostly around somata of other juxtaglomerular neurons, which were also small, non-dopaminergic and to a large extent non-GABAergic. Clasping SACs were observed also in wild-type mice and juvenile rats. In DAT+ SAC dendrites, single backpropagating action potentials evoked robust calcium entry throughout both clasping and non-clasping compartments. Besides clasping SACs, most other small neurons either corresponded to the classical periglomerular cell type (PGCs), which was never DAT+, or were undersized cells with a small dendritic tree and low excitability. Aside from the presence of clasps in SAC dendrites, many descriptors of dendritic morphology such as the number of dendrites and the extent of branching were not significantly different between clasping SACs and PGCs. However, a detailed morphometric analysis in relation to glomerular contours revealed that the dendrites of clasping SACs arborized mostly in the juxtaglomerular space and never entered more than one glomerulus (if at all), whereas most PGC dendrites were restricted to their parent glomerulus, similar to the apical tufts of mitral cells. These complementary arborization patterns might underlie a highly complementary functional connectivity. The morphometric approach may serve to differentiate also other subtypes of juxtaglomerular neurons, help to identify putative synaptic partners and thus to establish a more refined picture of glomerular network interactions during odor sensing.