Image Processing Software
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Author(s):  
Vicente Faus-Matoses ◽  
Eva Burgos Ibáñez ◽  
Vicente Faus-Llácer ◽  
Celia Ruiz-Sánchez ◽  
Álvaro Zubizarreta-Macho ◽  
...  

This study aimed at analyzing and comparing the ease of removal of fractured nickel–titanium (NiTi) endodontic rotary files from the root canal system between the ultrasonic tips and the Endo Rescue appliance removal systems, as well as comparing the volume of dentin removed between ultrasonic tips and the Endo Rescue appliance using a micro-computed tomography (micro-CT) scan. Material and Methods: Forty NiTi endodontic rotary files were intentionally fractured in 40 root canal systems of 20 lower first molar teeth and distributed into the following study groups: A: Ultrasonic tips (n = 20) (US) and B: Endo Rescue device (n = 20) (ER). Preoperative and postoperative micro-CT scans were uploaded into image processing software to analyze the volumetric variations of dentin using an algorithm that enables progressive differentiation between neighboring pixels after defining and segmenting the fractured NiTi endodontic rotary files and the root canal systems in both micro-CT scans. A non-parametric Mann–Whitney–Wilcoxon test or t-test for independent samples was used to analyze the results. Results: The US and ES study groups saw 8 (1 mesiobuccal and 7 distal root canal system) and 3 (distal root canal system) fractured NiTi endodontic rotary files removed, respectively. No statistically significant differences were found in the amount of dentin removed between the US and ER study groups at the mesiobuccal (p = 0.9109) and distal root canal system (p = 0.8669). Conclusions: Ultrasonic tips enable greater ease of removal of NiTi endodontic rotary files from the root canal system, with similar amounts of dentin removal between the two methods.


Author(s):  
Md Anowar Hossain

Chromatic and achromatic (AC) assessments of camouflage textiles have been critical to the defense researchers for concealment, detection, recognition, and identification (CDRI) of target signature against multidimensional combat background (CB). AC assessment and camouflage measurement techniques are simulated and experimented for assessment of camouflage textiles against CB. This model has been demonstrated for color measurement spectrophotometer, scanning electron microscopy (SEM), digital imaging, hyperspectral imaging, and image processing software (ImageJ) for the advancement and establishment of AC camouflage textiles assessment. The chromatic variations of 48 artificial target objects (TOBs) have been synthesized by image processing; the technique can be implemented for defense CB-CDRI assessment. Microstructural variation versus optical signal of woodland, desertland and stoneland CB materials have been elucidated by SEM magnification. The achromatic variation of CB materials have been demonstrated for the replacement of optical signal against modern remote sensing device to the imaging sensor. Color difference (Δ E), microstructural variations, pixel variations to imaging signal and standard deviation of CB materials have been represented for remote sensing surveillance of defense applications against TOB-CB-CDRI. Technical simulation of color, texture, gloss, and pixel intensity has been derived for AC-CDRI assessment of camouflage textiles in TOBs-CB environment.


2021 ◽  
Vol 14 (1) ◽  
pp. 20-25
Author(s):  
Meri Hamdini ◽  
Yuant Tiandho

Until now, the world is still facing the spread of the SARS-CoV-2 virus that causes COVID-19. This virus can be transmitted from human to human through droplets, so more vigilance is needed to avoid contracting this virus. One of the steps to minimize the spread of Covid-19 is to wear a face mask. In practice, most people prefer to use cloth masks than disposable medical masks because they are cheap and reusable. Cloth pore size influences the filtering ability of the cloth masks. Therefore, it is necessary to analyze the efficiencies of the cloth masks. In this study, we developed a method for measuring the pores of a cloth mask using a smartphone. In this study, we developed a method for measuring the pores of a cloth mask using a smartphone. We used the camera zoom application on a smartphone and analyzed the image using image processing software, ImageJ. We appliedHuang's algorithm to adjust the image binarization threshold then calculated the Feret diameter as the pore size of the mask. According to the analysis, the pore size ranged from 0.133 to 0.232 mm, and the efficiency ranged from 77.4 to 82.6%.


2021 ◽  
pp. 112070002110594
Author(s):  
Arun Kannan ◽  
Chameka Madurawe ◽  
Jim Pierrepont ◽  
Stephen McMahon

Background: The placement of uncemented acetabular components during total hip arthroplasty (THA) in Crowe II and Crowe III dysplasia can be at the anatomic or high hip centre position. Purposes: Using computerised tomography data, we simulated acetabular cup placement at the anatomic hip centre and the high hip centre positions to assess whether there is a difference between the 2 in terms of bone loss from acetabular reaming and in acetabular coverage by host bone. Methods: The study population included a consecutive cohort of 19 patients (22 hips) with Crowe II or III dysplasia. 3-dimensional models of the pelvis were created for each patient and digital templating was used to determine the anatomic and high hip centre positions. The coordinates of the digitally templated cup positions were fed into an image processing software to estimate the amount of bone reamed, the cup coverage by host bone and the elevation from tear drop. Results: The mean volume of bone reamed was greater in the high hip centre position as compared to the anatomic position (27.3 ± 11. 4 cm3 vs. 19.4 ± 12.2 cm3, p  < 0.0001). The coverage of the acetabular cup by host bone was greater in the high hip centre position (87.3 ± 5.9% vs. 68.3 ± 10%). The mean elevation in the high hip centre group was 13 mm with 3 hips having a breach of the medial wall. Conclusions: In Crowe II and III dysplasia, placement of acetabular cups at the anatomic hip centre better preserves bone stock as compared to high hip centre placement and should be preferred in young patients requiring THA.


OENO One ◽  
2021 ◽  
Vol 55 (4) ◽  
pp. 209-226
Author(s):  
Carlos Lopes ◽  
Jorge Cadima

Recent advances in machine vision technologies have provided a multitude of automatic tools for recognition and quantitative estimation of grapevine bunch features in 2D images. However, converting them into bunch weight (BuW) is still a big challenge. This paper aims to compare the explanatory power of the number of visible berries (#vBe) and the bunch area (BuA) in 2D images, in order to predict BuW. A set of 300 bunches from four grapevine cultivars were picked at harvest and imaged using a digital RGB camera. Then each bunch was manually assessed for several morphological attributes and, from each image, the #vBe was visually assessed while BuA was segmented using manual labelling combined with an image processing software. Single and multiple regression analysis between BuW and the image-based variables were performed and the obtained regression models were subsequently validated with two independent datasets.The high goodness of fit obtained for all the linear regression models indicates that either one of the image-based variables can be used as an accurate proxy of actual bunch weight and that a general model is also suitable. The comparison of the explanatory power of the two image-based attributes for predicting bunch weight showed that the models based on the predictor #vBe had a slightly lower coefficient of determination (R2) than the models based on BuA. The combination of the two image-based explanatory variables in a multiple regression model produced predictor models with similar or noticeably higher R2 than those obtained for single-predictor models. However, adding a second variable produced a higher and more generalised gain in accuracy for the simple regression models based on the predictor #vBe than for the models based on BuA. Our results recommend the use of the models based on the two image-based variables, as they were generally more accurate and robust than the single variable models. When the gains in accuracy produced by adding a second image-based feature are small, the option of using only a single predictor can be chosen; in such a case, our results indicate that BuA would be a more accurate and less cultivar-dependent option than the #vBe.


2021 ◽  
Author(s):  
◽  
Patrick Hipgrave

<p>Differentiating between species of plants in aerial imagery is often challenging and, in some cases, can be impossible without significant field data collection. However, remote sensing technology is developing to the point where it is increasingly possible to eliminate the need for extensive fieldwork entirely and conduct non-disruptive monitoring of fragile environments. The increasing availability of UAV platforms with integrated high-resolution cameras and low-cost image processing software is also making remote sensing operations accessible to those outside the scientific community with an interest in environmental monitoring. This project trialled an emerging set of image analysis techniques called ‘object-based image analysis’ to create fine scale maps of a recovering wetland area, based on aerial photographs collected using a consumer-grade UAV (unmanned aerial vehicle). The effects of including additional ancillary data (such as digital surface models (DSMs) and multispectral imagery) in the classification process were also assessed to compare the ability of a standard digital camera to produce high-accuracy classifications to that of a more specialised multispectral sensor. The inclusion of this extra information was found to significantly improve classification accuracy in almost all cases, making a strong argument for the inclusion of ancillary data whenever possible, especially when considering the ease with which ancillary datasets can be produced. The high-resolution (between 2 and 4cm/pixel) imagery provided sufficient detail to observe 28 distinct land cover classes in total, with around 20 classes per image. While the number of classes in the classification scheme may have imposed limits on the overall accuracy of the classified maps, several classes were classified with a high (70% or greater) level of accuracy, including two invasive species, showing that the object-based school of image classification has potential to be a powerful tool for detecting and tracking individual vegetation types.</p>


2021 ◽  
Author(s):  
◽  
Patrick Hipgrave

<p>Differentiating between species of plants in aerial imagery is often challenging and, in some cases, can be impossible without significant field data collection. However, remote sensing technology is developing to the point where it is increasingly possible to eliminate the need for extensive fieldwork entirely and conduct non-disruptive monitoring of fragile environments. The increasing availability of UAV platforms with integrated high-resolution cameras and low-cost image processing software is also making remote sensing operations accessible to those outside the scientific community with an interest in environmental monitoring. This project trialled an emerging set of image analysis techniques called ‘object-based image analysis’ to create fine scale maps of a recovering wetland area, based on aerial photographs collected using a consumer-grade UAV (unmanned aerial vehicle). The effects of including additional ancillary data (such as digital surface models (DSMs) and multispectral imagery) in the classification process were also assessed to compare the ability of a standard digital camera to produce high-accuracy classifications to that of a more specialised multispectral sensor. The inclusion of this extra information was found to significantly improve classification accuracy in almost all cases, making a strong argument for the inclusion of ancillary data whenever possible, especially when considering the ease with which ancillary datasets can be produced. The high-resolution (between 2 and 4cm/pixel) imagery provided sufficient detail to observe 28 distinct land cover classes in total, with around 20 classes per image. While the number of classes in the classification scheme may have imposed limits on the overall accuracy of the classified maps, several classes were classified with a high (70% or greater) level of accuracy, including two invasive species, showing that the object-based school of image classification has potential to be a powerful tool for detecting and tracking individual vegetation types.</p>


Author(s):  
Kaori Itto-Nakama ◽  
Shun Watanabe ◽  
Naoko Kondo ◽  
Shinsuke Ohnuki ◽  
Ryota Kikuchi ◽  
...  

Abstract Several industries require getting information of products as soon as possible during fermentation. However, the trade-off between sensing speed and data quantity presents challenges for forecasting fermentation product yields. In this study, we tried to develop AI models to forecast ethanol yields in yeast fermentation cultures, using cell morphological data. Our platform involves the quick acquisition of yeast morphological images using a non-staining protocol, extraction of high-dimensional morphological data using image processing software, and forecasting of ethanol yields via supervised machine learning. We found that the neural network algorithm produced the best performance, which had a coefficient of determination of &gt; 0.9 even at 30 and 60 min in the future. The model was validated using test data collected using the CalMorph-PC(10) system, which enables rapid image acquisition within 10 min. AI-based forecasting of product yields based on cell morphology will facilitate the management and stable production of desired biocommodities.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
M. Arza-García ◽  
C. Núñez-Temes ◽  
J. A. Lorenzana ◽  
J. Ortiz-Sanz ◽  
A. Castro ◽  
...  

AbstractDue to their cost, high-end commercial 3D-DIC (digital image correlation) systems are still inaccessible for many laboratories or small factories interested in lab testing materials. These professional systems can provide reliable and rapid full-field measurements that are essential in some laboratory tests with high-strain rate events or high dynamic loading. However, in many stress-controlled experiments, such as the Brazilian tensile strength (BTS) test of compacted soils, samples are usually large and fail within a timeframe of several minutes. In those cases, alternative low-cost methods could be successfully used instead of commercial systems. This paper proposes a methodology to apply 2D-DIC techniques using consumer-grade cameras and the open-source image processing software DICe (Sandia National Lab) for monitoring the standardized BTS test. Unlike most previous studies that theoretically estimate systematic errors or use local measures from strain gauges for accuracy assessment, we propose a contrast methodology with independent full-field measures. The displacement fields obtained with the low-cost system are benchmarked with the professional stereo-DIC system Aramis-3D (GOM GmbH) in four BTS experiments using compacted soil specimens. Both approaches proved to be valid tools for obtaining full-field measurements and showing the sequence of crack initiation, propagation and termination in the BTS, constituting reliable alternatives to traditional strain gauges. Mean deviations obtained between the low-cost 2D-DIC approach and Aramis-3D in measuring in-plane components were 0.08 mm in the perpendicular direction of loading (ΔX) and 0.06 mm in the loading direction (ΔY). The proposed low-cost approach implies considerable savings compared to commercial systems.


2021 ◽  
Vol 30 (11) ◽  
pp. 904-914
Author(s):  
Jennifer Ernst ◽  
Murat Tanyeli ◽  
Thomas Borchardt ◽  
Moses Ojugo ◽  
Andreas Helmke ◽  
...  

Objective: The response of different critical acute and hard-to-heal wounds to an innovative wound care modality—direct application of cold atmospheric plasma (CAP)—was investigated in this clinical case series. Method: Over an observation period of two years, acute wounds with at least one risk factor for chronification, as well as hard-to-heal wounds were treated for 180 seconds three times per week with CAP. CAP treatment was additional to standard wound care. Photographs were taken for wound documentation. The wound sizes before the first CAP treatment, after four weeks, after 12 weeks and at wound closure/end of observation time were determined using image processing software, and analysed longitudinally for the development of wound size. Results: A total of 27 wounds (19 hard-to-heal and eight acute wounds) with a mean wound area of 15cm2 and a mean wound age of 49 months were treated with CAP and analysed. All (100%) of the acute wounds and 68% of the hard-to-heal wounds healed after an average treatment duration of 14.2 weeks. At the end of the observation period, 21% of hard-to-heal wounds were not yet closed but were reduced in size by >80%. In 11% of the hard-to-heal wounds (n=2) therapy failed. Conclusion: The results suggested a beneficial effect of additional CAP therapy on wound healing. Declaration of interest: This work was carried out within the research projects ‘Plasma for Life’ (funding reference no. 13FH6I04IA) with financial support from the German Federal Ministry of Education and Research (BMBF). In the past seven years AFS has provided consulting services to Evonik and has received institutional support by Heraeus, Johnson & Johnson and Evonik. There are no royalties to disclose. The Department for Trauma Surgery, Orthopaedics and Plastic Surgery received charitable donations by CINOGY GmbH. CINOGY GmbH released the di_CAP devices and electrodes for the study. WV and AH were involved in the development of the used di_CAP device (Plasmaderm, CINOGY GmbH). WV is shareholder of the outsourced start-up company CINOGY GmbH.


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