Line Extraction Research Articles

Spine pathologies detections: users’ requirements, technological development and first results.

For spinal pathologies, especially scoliosis, early detection is essential to limit symptoms during growth and health impacts at skeletal maturity. Currently, school screening campaigns or annual medical visits are the main means of ensuring this detection. It is possible to attain a screening sensitivity of 93.8% and a sensibility of 99.2% by combining a Forward Bending Test, a scoliometer and Moiré’s topography, but due to a lack of time, of trained professionals or of access to specific tools, a majority of children are not screened.The objective of this research is to define the specifications of a massive and easy-to-use screening tool through a qualitative study to address this issue. A review of the literature, interviews and discussions with health professionals, particularly physiotherapists, helped to define the needs. Five physiotherapists and a pediatric rehabilitation physician were interviewed during semi-structured interviews. To extract the main categories of ideas and opinions expressed, the data were analyzed and coded using grounded theory. This step was intended to help us define requirements. The first results of the subsequently selected technical solution, a depth camera, and the associated software development will be presented. This prototype software for spine detection was developed and tested on an adult body.The interviews highlighted the relevance of a new tool for spine and back analysis. A tool that would provide processed information with high reliability and accuracy, combined with low cost and low processing time would be ideal for health professionals. To complement the tools already used by professionals, a solution that could give a dynamic visualization of the spine curve will be valuable. The solution developed uses a Kinect sensor capturing the patient’s back. The current software development allows the dynamic extraction of the spine line for the patient during the anterior flexion test (Adam’s test).

Evaluation of Anticancer Potential of Biogenic Copper Oxide Nanoparticles (CuO NPs) against Breast Cancer

The present study evaluated the anticancer potential of copper oxide nanoparticles (CuO NPs) synthesized from pumpkin seed extract in human breast cancer cell line (MDA‐MB‐231) using a battery of tests such as MTT [3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide] assay, morphological alteration, reactive oxygen species (ROS) generation, and changes in mitochondrial membrane potential (MMP). The biogenic CuO NPs showed a dose‐dependent decline in cell viability with 50% inhibitory concentration (IC50) at 20 μg/ml. Treatment with an IC50 dose of CuO NPs resulted in considerable morphology changes, such as shrinkage, detachment, membrane blebbing, and deformed shape in MDA‐MB‐231 cells. We also observed a significant dose‐dependent increase in ROS production and MMP modulation due to CuO NP treatment. Overall, CuO NPs showed significant anticancer potential in the breast cancer cell line. However, further validation of our data is required in ex vivo and in vivo models before this nanoformulation could be exploited for the treatment/management of human breast cancer.

Determination of the location of the needle entry point based on an improved pruning algorithm.

Since the emergence of new coronaviruses and their variant virus, a large number of medical resources around the world have been put into treatment. In this case, the purpose of this article is to develop a handback intravenous intelligence injection robot, which reduces the direct contact between medical staff and patients and reduces the risk of infection. The core technology of hand back intravenous intelligent robot is a handlet venous vessel detection and segmentation and the position of the needle point position decision. In this paper, an image processing algorithm based on U-Net improvement mechanism (AT-U-Net) is proposed for core technology. It is investigated using a self-built dorsal hand vein database and the results show that it performs well, with an F1-score of 93.91%. After the detection of a dorsal hand vein, this paper proposes a location decision method for the needle entry point based on an improved pruning algorithm (PT-Pruning). The extraction of the trunk line of the dorsal hand vein is realized through this algorithm. Considering the vascular cross-sectional area and bending of each vein injection point area, the optimal injection point of the dorsal hand vein is obtained via a comprehensive decision-making process. Using the self-built dorsal hand vein injection point database, the accuracy of the detection of the effective injection area reaches 96.73%. The accuracy for the detection of the injection area at the optimal needle entry point is 96.50%, which lays a foundation for subsequent mechanical automatic injection.

Study on spark discharge enhanced laser-induced breakdown spectroscopy of Fe particles in transformer oil

In the quantitative analysis of Fe particles in oil, spark discharge can effectively enhance the LOQ of LIBS by three times. The enhancement and extraction of analysis lines can be realized by adjusting charging conditions appropriately.

A Novel Rock-Mass Point Cloud Registration Method Based on Feature Line Extraction and Feature Point Matching

Registration will directly affect the quality of overall rock-mass point cloud, which is the basis of 3-D reconstruction for rock mass. Advanced methods establish correspondence by extracting various features that remain unchanged. Although these methods have made great progress, they analyze the local characteristics of each sample point, which leads to be inefficient. In this article, we select registration interesting points from feature lines that were extracted based on supervoxel and innovatively introduce the “clustering, primary matching, and coarse registration” strategy, which effectively reduces the complexity of calculating the corresponding relationship during point cloud registration. Finally, the iterative closest point (ICP) algorithm is used to optimize the result of coarse registration. By selecting registration interesting points from the extracted feature lines, the proposed method inherits the robustness of feature lines to noise, initial position, and so on. The experimental results prove that the coarse registration and refined registration results of the proposed method both have high accuracy and efficiency.

BS-McL: Bilevel Segmentation Framework With Metacognitive Learning for Detection of the Power Lines in UAV Imagery

In this article, we propose a bilevel segmentation framework with metacognitive learning (BS-McL) to detect power lines with an RGB camera mounted on an unmanned aerial vehicle (UAV) platform. The proposed framework consists of two levels based on spectral and spatial techniques. In the first level, spectral classification is carried out using the McL method, which is an evolving online learning neural network architecture. Due to similarities in spectral intensities, few nonpower line pixels are grouped along with power line pixels. The nonpower line pixels are removed by spatial segmentation in the second level. The second level includes morphological operations such as geometric features (shape and density indices), which are applied to detect the power lines. The processing steps of BS-McL are illustrated using a synthetic image of size <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$9 \times 6$ </tex-math></inline-formula> pixels. Also, two datasets consisting of 64 images with varying backgrounds, different locations, and dimensions of power lines are used to demonstrate the performance of the proposed BS-McL. The obtained results for BS-McL are compared with five commonly used methods. For both datasets, the efficiency of the BS-McL for power line extraction is better than for the methods used for comparison. Furthermore, the trained knowledge from our experimental set-up (Dataset 1: suburban scene) can be transferred to another dataset that is available publicly (Dataset 2: urban and mountain scenes) if the power line spectral values are in relevance with the distribution in the training dataset. The proposed approach BS-McL is based on online learning with a self-adaptive architecture, which provides improved generalization ability.

조선 중공업 환경 내 자율 용접 작업 경로 추출을 위한 특징 형상 인식 기법

Many research and development for the autonomous welding have been progressed. It is necessary to extract trajectory lines from the workpieces for welding automation, and various sensors such as laser sensors have been studied. In this study, we propose a vision-based guidance line extraction method for autonomous welding robot systems. The proposed method uses a series of image processes for extracting welding trajectory data. To verify our method, we constructed test beds based on CAD data in heavy industries and conducted several experiments. These experiments confirmed the applicability of our method, which has advantages in terms of speed and cost for automatic welding in heavy industries.

Effective Text Processing utilizing NLP

Summarizing is the practice of condensing a body of material into a more manageable size while retaining all of the key data elements and the intended meaning. Automatic text summarizing systems can now quickly retrieve summary phrases from input documents. However, it has a number of shortcomings, such as duplication, insufficient coverage, incorrect extraction of key lines, and poor sentence coherence. In this study, a new concept of summarizer technique is proposed using the Python spacy package. It extracts the most significant information from the text. The scoring system is also used to compute the score for the words in order to determine the word frequency. The findings show that the proposed method completes the summary process faster than the current algorithm. An online tool called the text to summary converter aids in material summarizing. This programmer will give us a summary of the data that we upload. The primary goal is to accurately summaries the data entered. The most crucial sentences will be removed before the unnecessary ones.

Evaluation of Anticancer Effect of Lippia nodiflora Leaf Extract on Lung Cancer Cells

Background: Lung cancer, also known as bronchogenic carcinoma, is a kind of cancer that begins in the lung parenchyma or inside the bronchi. In the United States, it is one of the top causes of cancer-related fatalities. Lippia nodiflora is a flowering, broadleaf plant native to South America. Lippia nodiflora has been used as a natural medicine for a number of disorders due to its antioxidant, anti-inflammatory, anti-bacterial, and anti-tumor characteristics.&#x0D; Aim of the Study: To evaluate the anticancer effect of Lippia nodiflora leaf extract on lung cancer.&#x0D; Materials and methods: The cytotoxic effect of Lippia nodiflora leaf extract was assessed by an MTT assay. The A-549 cells were treated with different concentrations of Lippia nodiflora leaf extract (10-120 μg) for 24h. Analysis of changes in the cell morphology is examined by phase contrast microscope. For the nuclear morphological changes analysis, DAPI staining was used in lung cancer cells. The apoptotic nuclei were viewed under a fluorescent microscope.&#x0D; Results: In our study, Lippia nodiflora leaf extract treated cells showed significant reduction of cell viability in lung cancer cells. 50% of the inhibition was observed in a 20 μg/ml concentration, which has been taken as the inhibitory concentration (IC-50) which was used for further analyses. The pro-apoptotic effect of Lippia nodiflora leaf extract in A549 cell line was determined by DAPI staining under a fluorescence microscope. Lippia nodiflora leaf extract treatment alters the nuclear morphology and condensed nuclei in lung cancer cells at 20μg/ml concentration.&#x0D; Conclusion: Overall, it can be concluded that Lippia nodiflora presents anticancer activity at 20μg/ml concentration at 24 hrs againstthe lung cancer cell line. However, further research is warrented to find out the molecular mechanism of cytotoxicity of effect this plant extract against lung cancer.

Lane Line Extraction in Raining Weather Images by Ridge Edge Detection with Improved MSR and Hessian Matrix

To accurately detect lane lines in road traffic images at raining weather, a edge detection based method is studied, which mainly includes four algorithms. (1) Firstly an image is enhanced by an improved Retinex algorithm; (2) Then, an algorithm based on the Hessian matrix is applied to strengthen lane lines; (3) To extract the feature points of a lane line, a ridge edge detection algorithm based on five line detection in four directions is proposed, in which, in light on the possible positions of lane lines in the image, it detects the maximum gray level points in the local area of the detecting point within the pre-set valid detection region; and (4) After the noise removal based on the minimum circumscribed rectangles, the candidate points of lane lines are connected as segments, and for the gap filling between segments, in order to make connection correctly, the algorithm makes the filling in two steps, short gap and long gap fillings, and the long gap filling is made on the combination of segment angle difference and gap distance and gap angle. By testing hundreds of images of the lane lines at raining weather and by comparing several traditional image enhancement and segmentation algorithms, the new method of the lane line detection can produce the satisfactory results.

ANTICANCER ACTIVITY OF NATURAL COMPOUND FROM LEMON GRASS LEAVES EXTRACT ON LUNG CARCINOMA CELL LINE A549: AN IN VITRO STUDY

Lemon grass is a widely cultivated plant, whose extracts are known to possess anti-cancer properties. However, studies related to the effect of different solvent extracts of lemon grass on lung cancer cell lines are scarce. This study was conducted to study the effect of various extracts on the viability of the A549 lung carcinoma cell line. Four solvents (hexane, chloroform, ethyl acetate and ethanol) were used for extraction of lemon grass. The effect of these solvent extracts on A549 cell line was studied. Cell viability was studied by 3-(4,5-Dimethylthiazol-2-Yl)-2,5-Diphenyltetrazolium Bromide (MTT) method. The effect of apoptosis on exposure to aforementioned extracts was observed with help of nuclear staining assays and western blotting techniques. Apoptosis was confirmed by nuclear staining using acridine orange ethidium bromide (Ao/EtBr), while pro- and anti-apoptotic cells expressions analysis was conducted using western blotting. All extracts showed cytotoxicity on lung carcinoma cell line, wherein, ethyl acetate and hexane extracts showed up to 48.6±3.8% and 51.7±1.7% viability at 250µg/mL concentration. Up regulation of pro-apoptotic gene expressions like Caspase-3 and inhibition of anti-apoptotic gene expression like Bcl-2 was observed after 24h. An inhibitory concentration (IC50) of 220.01 µg/mL was obtained for the ethyl acetate extract. When observed under fluorescence microscope, stained cells showed an orange red color in the nuclei, indicating the ethyl acetate extract had induced apoptosis potentially for 24 h exposure cells expression, when compared with control cells. The results show that the ethyl acetate extracts were efficient in inhibiting the A549 cell line under in vitro condition, suggesting this extract can be further used as a potential chemotherapy drug.

Enhancing Coherence Images for Coherent Change Detection: An Example on Vehicle Tracks in Airborne SAR Images

In Synthetic Aperture Radar (SAR) interferometry, one of the most widely used measures for the quality of the interferometric phase is coherence. However, in favorable conditions coherence can also be used to detect subtle changes on the ground, which are not visible in the amplitude images. For such applications, i.e., coherent change detection, it is important to have a good contrast between the unchanged (high-coherence) parts of the scene and the changed (low-coherence) parts. In this paper, an algorithm is introduced that aims at enhancing this contrast. The enhancement is achieved by a combination of careful filtering of the amplitude images and the interferometric phase image. The algorithm is applied to an airborne interferometric SAR image pair recorded by the SmartRadar experimental sensor of Hensoldt Sensors GmbH. The data were recorded during a measurement campaign over the Bann B installations of POLYGONE Range in southern Rhineland-Palatinate (Germany), with a time gap of approximately four hours between the overflights. In-between the overflights, several vehicles were moved on the site and the goal of this work is to enhance the coherence image such that the tracks of these vehicles can be detected as completely as possible in an automated way. Several coherence estimation schemes found in the literature are explored for the enhancement, as well as several commonly used speckle filters. The results of these filtering steps are evaluated visually and quantitatively, showing that the mean gray-level difference between the low-coherence tracks and their high-coherence surroundings could be enhanced by at least 28%. Line extraction is then applied to the best enhancement. The results show that the tracks can be detected much more completely using the coherence contrast enhancement scheme proposed in this paper.

Extraction and registration of 3D lines by fusing gradient information and neighboring point cloud distribution

The traditional point-based scene reconstruction scheme always leads to inaccurate 3D reconstruction results due to its lack of scene texture and object occlusions. With the help of geometric characteristics and line features of 3D point cloud scenes, a novel extraction, matching, and registration method of 3D line features is presented by fusing RGB gradients and the spatial distribution of neighboring point clouds. Firstly, the supporting region of 3D linear segments with similar gradient directions can be determined by the gradients of an RGB scene image. Secondly, owing to the neighboring geometric features contained in the depth map, the point set of boundary lines and folded edge lines can also be extracted according to the spatial distribution of the current point and its neighboring points. The 3D line features can thus be fitted by these extracted point sets respectively. Thirdly, taking each extracted 3D line feature as a central axis, the supporting region can be constructed as the co-axial cylinder with the same thickness of each cylindrical layer. According to the 3D gradient statistics of point cloud within each cylindrical layer, we can calculate an intrinsic descriptor for each 3D line, which can be adopted to match 3D line features between scene frames. Finally, a novel line-to-line iterative closest line registration algorithm is introduced to compute the rotation and translation transformations, and the inter-frame point cloud scene data can be registered efficiently. The experimental results illustrate that the proposed line feature-based scheme has high registration efficiency, less computational cost, accurate registration, and strong robustness when compared with the existing line feature extraction and point-based registration methods.

Effects of 5',8'-Cyclo-2'-Deoxypurines on the Base Excision Repair of Clustered DNA Lesions in Nuclear Extracts of the XPC Cell Line.

Clustered DNA lesions (CDL) containing 5′,8-cyclo-2′-deoxypurines (cdPus) are an example of extensive abnormalities occurring in the DNA helix and may impede cellular repair processes. The changes in the efficiency of nuclear base excision repair (BER) were investigated using (a) two cell lines, one of the normal skin fibroblasts as a reference (BJ) and the second from Xeroderma pigmentosum patients’ skin (XPC), and (b) synthetic oligonucleotides with single- and double-stranded CDL (containing 5′,8-cyclo-2′-deoxyadenosine (cdA) and the abasic (AP) site at various distances between lesions). The nuclear BER has been observed and the effect of both cdA isomers (5′R and 5′S) presence in the DNA was tested. CdPus affected the repair of the second lesion within the CDL. The BER system more efficiently processed damage in the vicinity of the ScdA isomer and changes located in the 3′-end direction for dsCDL and in the 5′-end direction for ssCDL. The presented study is the very first investigation of the repair processes of the CDL containing cdPu considering cells derived from a Xeroderma pigmentosum patient.

Robot line structured light vision measurement system: light strip center extraction and system calibration

We investigate the light strip center extraction and system calibration method of a robot line structured light vision measurement system to realize fast on-line measurement of complex objects. First, the model of a robot vision measurement system is established to analyze the key technologies involved for improving the measurement accuracy of the system. Second, on the basis of the traditional gray gravity method, a gray gravity method based on the normal direction is proposed to extract the center of the laser stripe. Considering the influence of camera distortion, the accuracy of extracting the center stripe can be further improved. Third, a two-dimensional checkerboard is applied to synchronously calibrate the camera parameters, laser plane parameters, and hand-eye relationship of the robot, thus improving the efficiency and accuracy of system calibration. Finally, three-dimensional topography and the geometric dimensions of a complex part are measured by the constructed system with high accuracy. The experimental results show that the average measurement error is <0.2 mm and the measurement accuracy is <1.3 % , indicating that the system can be effectively used in actual industrial measurement.

Spectral line extraction based on ant-colony algorithm

A spectral-line-extraction algorithm based on the ant-colony algorithm is proposed to address the difficulty of extracting spectral lines in low signal-to-noise ratio conditions, and the problem that results from the optimal path algorithm falls into local optimization. The algorithm applies the ant-colony path-optimization strategy to detect a spectral line and constructs a corresponding mathematical model using the grid method. A new cost function is proposed to replace path length as the optimization standard in the conventional ant-colony algorithm. At the same time, the roulette rule is used to determine the direction of the next step. This algorithm improves the traditional heuristic function, increases the attraction of the target spectral line to the route search, and improves the convergence rate. Sea-trial data show that the algorithm performs better in extracting spectral lines with a low signal-to-noise ratio than the optimal path algorithm.

Antiallergic activities of Japanese leaf burdock extract in a rat basophilic leukemia cell line.

Although primarily cultivated for its edible root, the leaves and stems of "Japanese leaf burdock (Arctium lappa L)" are also edible. This study determined the antiallergic activity of root, leaf, and stem extracts of Japanese leaf burdock using the rat basophilic leukemia cell line. We demonstrate that the hot water extract of Japanese leaf burdock stems has a strong inhibitory effect on antigen-stimulated degranulation. This extract was further fractionated into five fractions using a glass column. The fraction obtained with 99% ethanol extracts (99% EtEx) elicits a concentration-dependent increase in degranulation inhibition. One of antiallergic compounds from the separation of components of the 99% EtEx fraction using high-performance liquid chromatography and mass spectrometry analyses had a value of m/z 393.16. From these results and those of previous studies, one of the antiallergic components was hypothesized to be onopordopicrin. Our findings demonstrate that the extract of Japanese leaf burdock exerts a strong antiallergic activity. PRACTICAL APPLICATIONS: "Japanese leaf burdock (Arctium lappa L)" is a traditional Japanese vegetable with edible leaves and stems. The antiallergic activity of the hot water extracts has been shown in vitro. One of the antiallergic components was hypothesized to be onopordopicrin. Therefore, "Japanese leaf burdock" could serve as a functional food for patients with allergic disorders, such as allergic rhinitis.

A Robust Model Fitting-based Method for Transmission Line Extraction from Airborne LiDAR Point Cloud Data

A Robust Model Fitting-based Method for Transmission Line Extraction from Airborne LiDAR Point Cloud Data

Polygonization method for automatic generation of indoor and outdoor pedestrian navigation path for smart city

Smart mobility cannot be supported by smart technologies alone. It has to be supported by geospatial data with navigation lines. Manual methods for creating and updating them are not only costly but also time-consuming. Automatic extraction and updating of geospatial navigation lines from GIS and indoor layout plans are much needed. The navigation path is often stored and conceived as centreline graphs in GIS. However, navigation paths in which the centrelines are located can be considered as a combination of basic navigation polygons. This paper proposed a generic polygonization method that can automatically generate and update navigation centrelines from GIS and BIM. By constructing basic navigation polygons from GIS and decomposing path polygons in street layouts and floor plans from GIS and BIM into basic navigation polygons, indoor and outdoor pedestrian navigation paths and centrelines can be extracted and generated to be used for indoor and outdoor pedestrian navigation.

Analysis of Temporal and Spatial Variability of Fronts on the Amery Ice Shelf Automatically Detected Using Sentinel-1 SAR Data

The Amery Ice Shelf (AIS) dynamics and mass balance caused by iceberg calving and basal melting are significant in the ocean climate system. Using satellite imagery from Sentinel-1 SAR, we monitored the temporal and spatial variability of the frontal positions on the Amery Ice Shelf, Antarctica, from 2015 to 2021. In this paper, we propose an automatic algorithm based on the SO-CFAR strategy and a profile cumulative method for frontal line extraction. To improve the accuracy of the extracted frontal lines, we developed a framework combining the Constant False Alarm Rate (CFAR) and morphological image-processing strategies. A visual comparison between the proposed algorithm and state-of-the-art algorithm shows that our algorithm is effective in these cases including rifts, icebergs, and crevasses as well as ice-shelf surface structures. We present a detailed analysis of the temporal and spatial variability of fronts on AIS that we find, an advance of the AIS frontal line before the D28 calving event, and a continuous advance after the event. The study reveals that the AIS extent has been advanced at the rate of 1015 m/year. Studies have shown that the frontal location of AIS has continuously expanded. From March 2015 to May 2021, the frontal location of AIS expanded by 6.5 km; while the length of the AIS frontal line is relatively different after the D28 event, the length of the frontal line increased by about 7.5% during 2015 and 2021 (255.03 km increased to 273.5 km). We found a substantial increase in summer advance rates and a decrease in winter advance rates with the seasonal characteristics. We found this variability of the AIS frontal line to be in good agreement with the ice flow velocity.