Segmentation of Tuberculosis Bacilli Using Watershed Transformation and Fuzzy C-Means

2019 ◽  
Vol 13 (1) ◽  
pp. 9
Author(s):  
Rahadian Kurniawan ◽  
Izzati Muhimmah ◽  
Arrie Kurniawardhani ◽  
Sri Kusumadewi
Keyword(s):  
Microscopic Analysis ◽  
High Accuracy ◽  
Kappa Coefficient ◽  
Field Of View ◽  
Resistant Bacteria ◽  
Screening Process ◽  
Watershed Transformation ◽  
Fuzzy C Means ◽  
Primary Health ◽  
Manual Calculation

The easily transmitted Tuberculosis (TB) disease is attributed to the fact that Mycobacterium Tuberculosis (MTB) bacteria/viruses can be transmitted through the air. One of the methods to screen the TB disease is by reading sputum slides. Sputum slides are colored sputum samples of TB patients placed on microscopic slides. However, TB disease microscopic analysis has some limitations since it requires high accuracy reading and well-trained health personnel to avoid errors in the process of interpretation. Furthermore, the number of TB patients in the Primary Health Care (PHC) and the process of manual calculation of bacteria in a field of view often complicate the decision-making in the screening process conducted by the medical staffs. In this paper, the researchers propose the use of Watershed Transformation and Fuzzy C-Means combination to help solve the problem. The researchers collect the photo shooting of three PHC in Indonesia with 55 images of sputum from different TB patients. The assessed results of the proposed method are compared with the opinions of three Microbiology doctors. The comparison shows Cohen’s Kappa Coefficient value of 0.838. It suggests that the proposed method can detect Acid Resistant Bacteria (ARB) although it needs some improvement to achieve higher accuracy.

scholarly journals Donor Screening for Fecal Microbiota Transplantation

2020 ◽  
Vol 95 (3) ◽  
pp. 181-187
Author(s):  
Han Hee Lee ◽  
Young-Seok Cho
Keyword(s):  
Randomized Clinical Trials ◽  
Fecal Microbiota Transplantation ◽  
Case Series ◽  
Fecal Microbiota ◽  
Resistant Bacteria ◽  
Screening Process ◽  
Antibiotic Resistant ◽  
Donor Screening ◽  
Large Case Series ◽  
Large Case

Fecal microbiota transplantation (FMT), which has been established as the standard treatment for recurrent <i>Clostroides</i> difficile infection, may also play a role in the management of other diseases associated with dysbiosis of the gut microbiota. To ensure efficacy and safety of FMT, an appropriate donor screening process is required. The main purpose of donor screening is to check for infectious diseases that could be transmitted to the recipient. The screening process involves a medical history questionnaire, and blood and stool testing. Several randomized clinical trials and large case series on FMT reported no, or few, adverse events related to infection by following this donor screening process. However, there is still concern over the transmission of antibiotic-resistant bacteria. In addition, a low donor acceptance rate due to rigorous screening makes donor recruitment difficult, and also imposes a significant cost burden. A consensus on the most crucial elements of donor screening is needed for wide application of FMT.

Protein-stabilized silver nanoparticles encapsulating gentamycin for the therapy of bacterial biofilm infections

Nanomedicine ◽  
2021 ◽  
Author(s):  
Sudip Nag ◽  
Arpita Biswas ◽  
Dhrubajyoti Chattopadhyay ◽  
Maitree Bhattacharyya
Keyword(s):  
Silver Nanoparticles ◽  
Bacterial Infections ◽  
Microscopic Analysis ◽  
Bacterial Biofilm ◽  
Resistant Bacteria ◽  
Hydrodynamic Diameter ◽  
Drug Resistant ◽  
Electron Microscopic ◽  
Antibacterial Efficiency ◽  
Control Drug

Aim: An antibiotic-conjugated protein-stabilized nanoparticle hybrid system was developed to combat the challenges faced during the treatment of drug-resistant bacterial biofilm-associated infections. Materials & methods: Biocompatible silver nanoparticles were synthesized using intracellular protein and gentamycin was attached. The resulting nanohybrid was characterized and its antibacterial efficiency was assessed against Gram-positive, Gram-negative and drug-resistant bacteria. Results: Spectroscopic and electron microscopic analysis revealed that the nanoparticles were spherical with a diameter of 2–6 nm. Red-shifting of the surface plasmon peak and an increase in hydrodynamic diameter confirmed attachment of gentamycin. The nanohybrid exhibited antibacterial efficiency against a range of bacteria with the ability to inhibit and disrupt bacterial biofilm. Conclusion: A unique nanohybrid was designed that has potential to be used to control drug-resistant bacterial infections in the future.

scholarly journals Revisiting Abell 2744: a powerful synergy of GLASS spectroscopy and HFF photometry

2015 ◽  
Vol 11 (A29B) ◽  
pp. 776-778
Author(s):  
Xin Wang ◽  
Keyword(s):  
Mass Distribution ◽  
Galaxy Cluster ◽  
Adaptive Mesh ◽  
Field Of View ◽  
Relative Distribution ◽  
Lens Model ◽  
Photometric Redshifts ◽  
Screening Process ◽  
Photometric Redshift ◽  
Extensive Analysis

AbstractWe present new emission line identifications and improve the lensing reconstruction of the mass distribution of galaxy cluster Abell 2744 using the Grism Lens-Amplified Survey from Space (GLASS) spectroscopy and the Hubble Frontier Fields (HFF) imaging. We performed blind and targeted searches for faint line emitters on all objects, including the arc sample, within the field of view (FoV) of GLASS prime pointings. We report 55 high quality spectroscopic redshifts, 5 of which are for arc images. We also present an extensive analysis based on the HFF photometry, measuring the colors and photometric redshifts of all objects within the FoV, and comparing the spectroscopic and photometric redshift estimates. In order to improve the lens model of Abell 2744, we develop a rigorous algorithm to screen arc images, based on their colors and morphology, and selecting the most reliable ones to use. As a result, 25 systems (corresponding to 72 images) pass the screening process and are used to reconstruct the gravitational potential of the cluster pixellated on an adaptive mesh. The resulting total mass distribution is compared with a stellar mass map obtained from the Spitzer Frontier Fields data in order to study the relative distribution of stars and dark matter in the cluster.

On-Orbit Calibration Approach Based on Partial Calibration-Field Coverage for the GF-1/WFV Camera

2019 ◽  
Vol 85 (11) ◽  
pp. 815-827 ◽  
Author(s):  
Mi Wang ◽  
Beibei Guo ◽  
Ying Zhu ◽  
Yufeng Cheng ◽  
Chenhui Nie
Keyword(s):  
High Resolution ◽  
High Accuracy ◽  
Field Of View ◽  
Estimation Methods ◽  
Large Field ◽  
Wide Field ◽  
Optical Remote Sensing ◽  
Calibration Data ◽  
Stereoscopic Images ◽  
Wide Field Of View

The Gaofen-1 (GF1) optical remote sensing satellite is the first in China's series of high-resolution civilian satellites and is equipped with four wide-field-of-view cameras. The cameras work together to obtain an image 800 km wide, with a resolution of 16 m, allowing GF1 to complete a global scan in four days. To achieve high-accuracy calibration of the wide-field-of-view cameras on GF1, the calibration field should have high resolution and broad coverage based on the traditional calibration method. In this study, a GF self-calibration scheme was developed. It uses partial reference calibration data covering the selected primary charge-coupled device to achieve high-accuracy calibration of the whole image. Based on the absolute constraint of the ground control points and the relative constraint of the tie points of stereoscopic images, we present two geometric calibration models based on paired stereoscopic images and three stereoscopic images for wide-field-of-view cameras on GF1, along with corresponding stepwise internal-parameter estimation methods. Our experimental results indicate that the internal relative accuracy can be guaranteed after calibration. This article provides a new approach that enables large-field-of-view optical satellites to achieve high-accuracy calibration based on partial calibration-field coverage.

scholarly journals Evaluation of Cyclosaplin Efficacy Using a Silk Based 3D Tumor Model

Biomolecules ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 123 ◽  
Author(s):  
Abheepsa Mishra ◽  
Sourav K Mukhopadhyay ◽  
Satyahari Dey
Keyword(s):  
Breast Cancer ◽  
Cell Mass ◽  
3D Culture ◽  
Microscopic Analysis ◽  
Tumor Model ◽  
Rapid Screening ◽  
Screening Process ◽  
3D Microenvironment ◽  
Anti Cancer

Development of novel anti-cancer peptides requires a rapid screening process which can be accelerated by using appropriate in vitro tumor models. Breast carcinoma tissue is a three-dimensional (3D) microenvironment, which contains a hypoxic center surrounded by dense proliferative tissue. Biochemical clues provided by such a 3D cell mass cannot be recapitulated in conventional 2D culture systems. In this experiment, we evaluate the efficacy of the sandalwood peptide, cyclosaplin, on an established in vitro 3D silk breast cancer model using the invasive MDA-MB-231 cell line. The anti-proliferative effect of the peptide on the 3D silk tumor model is monitored by alamarBlue assay, with conventional 2D culture as control. The proliferation rate, glucose consumed, lactate dehydrogenase (LDH), and matrix metalloproteinase 9 (MMP-9) activity of human breast cancer cells are higher in 3D constructs compared to 2D. A higher concentration of drug is required to achieve 50% cell death in 3D culture than in 2D culture. The cyclosaplin treated MDA-MB-231 cells showed a significant decrease in MMP-9 activity in 3D constructs. Microscopic analysis revealed the formation of cell clusters evenly distributed in the scaffolds. The drug treated cells were less in number, smaller and showed unusual morphology. Overall, these findings indicate the role of cyclosaplin as a promising anti-cancer therapeutic.

Error analysis and optimal design of reduction relay lens for field of view stitching applications

Sensor Review ◽  
2021 ◽  
Vol 41 (1) ◽  
pp. 87-92
Author(s):  
Xinjie Zhang ◽  
Fansen Kong ◽  
Zhiyuan Gu ◽  
Xiao Shen
Keyword(s):  
Remote Sensing ◽  
Image Quality ◽  
High Accuracy ◽  
Structure Design ◽  
Reduction Ratio ◽  
Field Of View ◽  
Machining Accuracy ◽  
Optical Remote Sensing ◽  
Optical Elements ◽  
Content Type

Purpose FOV splicing optical remote sensing instruments have a strict requirement for the focal length consistency of the lens. In conventional optical-mechanical structure design, each optical element is equally distributed with high accuracy and everyone must have a high machining and assembly accuracy. For optical remote sensors with a large number of optical elements, this design brings great difficulties to lens manufacture and alignment. Design/methodology/approach Taking the relay lens in an optical remote sensing instrument with the field of view splicing as an example, errors of the system are redistributed to optical elements. Two optical elements, which have the greatest influence on modulation transfer function (MTF) of the system are mounted with high accuracy centering and the other elements are fixed by gland ring with common machining accuracy. The reduction ratio consistency difference among lenses is compensated by adjusting the optical spacing between the two elements. Findings Based on optical system simulation analysis, the optimized structure can compensate for the difference of reduction ratio among lens by grinding the washer thickness in the range of ±0.37 mm. The test data for the image quality of the lens show that the MTF value declined 0.043 within ±0.4 mm of space change between two barrels. The results indicate that the reduction ratio can be corrected by adjusting the washer thickness and the image quality will not obviously decline. Originality/value This paper confirms that this work is original and has not been published elsewhere nor is it currently under consideration for publication elsewhere. In this paper, the optimum structural design of the reduction relay lens for the field of view stitching applications is reported. The method of adjusting washer thickness is applied to compensate for the reduction ratio consistency difference of lenses. The optimized structure also greatly reduces the difficulty of lenses manufacture, alignment and improves the efficiency of assembly.

Analyzing the Optimal Performance of Pest Image Segmentation using Non Linear Objective Assessments

2016 ◽  
Vol 6 (6) ◽  
pp. 2789 ◽  
Author(s):  
Siva Sangari A ◽  
Saraswady D
Keyword(s):  
Image Segmentation ◽  
Signal To Noise Ratio ◽  
Random Noise ◽  
Objective Assessment ◽  
Absolute Error ◽  
Agricultural Field ◽  
Watershed Transformation ◽  
Fuzzy C Means ◽  
Plant Cultivation ◽  
Fuzzy C Means Algorithm

<p>In modern agricultural field, pest detection is a major role in plant cultivation. In order to increase the Production rate of agricultural field, the presence of whitefly pests which cause leaf discoloration is the major problem.  This emphasizes the necessity of image segmentation, which divides an image into parts that have strong correlations with objects to reflect the actual information collected from the real world. Image processing is affected by illumination conditions, random noise and environmental disturbances due to atmospheric pressure or temperature fluctuation. The quality of pest images is directly affected by atmosphere medium, pressure and temperature. The fuzzy c means (FCM) have been proposed to identify accurate location of whitefly pests. The watershed transform has interesting properties that make it useful for many different image segmentation applications: it is simple and intuitive, can be parallelized, and always produces a complete division of the image. However, when applied to pest image analysis, it has important drawbacks (over segmentation, sensitivity to noise). In this paper, pest image segmentation using marker controlled watershed segmentation is presented. Objective of this paper is segmenting the pest image and comparing the results of fuzzy c means algorithm and marker controlled watershed transformation. The performance of an image segmentation algorithms are compared using nonlinear objective assessment or the quantitative measures like structural content, peak signal to noise ratio, normalized correlation coefficient, average difference and normalized absolute error. Out of the above methods the experimental results show that fuzzy c means algorithm performs better than watershed transformation algorithm in processing pest images.</p>

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