scholarly journals Smartphone-Enabled Quantification of Potassium in Blood Plasma

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4751
Author(s):  
Achmad Syarif Hidayat ◽  
Hideyuki Horino ◽  
Izabela I. Rzeznicka
Keyword(s):  
Blood Plasma ◽  
Low Cost ◽  
Color Space ◽  
Image Data ◽  
Mean Value ◽  
Image Processing Algorithm ◽  
Fresh Blood ◽  
Hsv Color Space ◽  
K Concentration ◽  
In Blood Plasma

This work describes a new method for determining K+ concentration, [K+], in blood plasma using a smartphone with a custom-built optical attachment. The method is based on turbidity measurement of blood plasma solutions in the presence of sodium tetraphenylborate, a known potassium precipitating reagent. The images obtained by a smartphone camera are analyzed by a custom image-processing algorithm which enables the transformation of the image data from RGB to HSV color space and calculation of a mean value of the light-intensity component (V). Analysis of images of blood plasma containing different amounts of K+ reveal a correlation between V and [K+]. The accuracy of the method was confirmed by comparing the results with the results obtained using commercial ion-selective electrode device (ISE) and atomic absorption spectroscopy (AAS). The accuracy of the method was within ± 0.18 mM and precision ± 0.27 mM in the [K+] range of 1.5–7.5 mM when using treated blood plasma calibration. Spike tests on a fresh blood plasma show good correlation of the data obtained by the smartphone method with ISE and AAS. The advantage of the method is low cost and integration with a smartphone which offers possibility to measure [K+] on demand and in remote areas where access to hospitals is limited.

scholarly journals A G-Fresnel Optical Device and Image Processing Based Miniature Spectrometer for Mechanoluminescence Sensor Applications

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3528 ◽  
Author(s):  
Min ◽  
Kim ◽  
Song ◽  
Kim
Keyword(s):  
Image Processing ◽  
Visible Light ◽  
Color Space ◽  
Image Sensor ◽  
Processing Algorithm ◽  
Image Processing Algorithm ◽  
Spectral Image ◽  
Optical Device ◽  
Hsv Color Space ◽  
Color Space Conversion

This paper presents a miniature spectrometer fabricated based on a G-Fresnel optical device (i.e., diffraction grating and Fresnel lens) and operated by an image-processing algorithm, with an emphasis on the color space conversion in the range of visible light. The miniature spectrometer will be cost-effective and consists of a compact G-Fresnel optical device, which diffuses mixed visible light into the spectral image and a μ-processor platform embedded with an image-processing algorithm. The RGB color space commonly used in the image signal from a complementary metal–oxide–semiconductor (CMOS)-type image sensor is converted into the HSV color space, which is one of the most common methods to express color as a numeric value using hue (H), saturation (S), and value (V) via the color space conversion algorithm. Because the HSV color space has the advantages of expressing not only the three primary colors of light as the H but also its intensity as the V, it was possible to obtain both the wavelength and intensity information of the visible light from its spectral image. This miniature spectrometer yielded nonlinear sensitivity of hue in terms of wavelength. In this study, we introduce the potential of the G-Fresnel optical device, which is a miniature spectrometer, and demonstrated by measurement of the mechanoluminescence (ML) spectrum as a proof of concept.

Rapid HPLC Method for Measurement of Vitamin D3 and 25(OH)D3 in Blood Plasma

2003 ◽  
Vol 73 (1) ◽  
pp. 15-18 ◽  
Author(s):  
A. A. Olkowski ◽  
G. Aranda-Osorio ◽  
J. McKinnon
Keyword(s):  
Vitamin D ◽  
Blood Plasma ◽  
High Performance ◽  
Low Cost ◽  
Hplc Method ◽  
Single Step ◽  
Physiological Status ◽  
Better Than ◽  
Hydroxy Metabolite ◽  
In Blood Plasma

The present work describes a novel, simplified high-performance liquid chromatography (HPLC) method for evaluation of vitamin D3 and its 25-hydroxy metabolite in blood plasma. The retrieval of the analytes from the blood plasma matrix is based on a single-step extraction using acetonitrile. The method is specific, sensitive, and ensures good reproducibility. The recovery of the analytes, precision, and reproducibility obtained using the present approach gave results comparable to or better than more complex, laborious, and time-consuming procedures. This method is suitable for evaluation of the host’s vitamin D physiological status, as well as for rapid analysis of blood plasma samples in suspected cholecalciferol toxicity. With a significantly shortened time of analysis (10 minutes), the present method allows the possibility for processing of a large number of samples rapidly, efficiently, and at a low cost.

scholarly journals Load Position Detection of Container Crane Using Camera

2021 ◽  
Vol 31.2 (149) ◽  
pp. 65-71
Keyword(s):  
Image Processing ◽  
Color Space ◽  
Processing Algorithm ◽  
Image Processing Algorithm ◽  
Camera System ◽  
Hsv Color Space ◽  
Container Cranes ◽  
Container Crane ◽  
Position Detection ◽  
Main Input

In this study, the authors proposed an image processing algorithm to detect (measure) the rope length of container crane (distance from camera system to container spreader) and sway angle of the spearder (container). This measurement will be the main input to design the anti-sway control system for container cranes. The image processing algorithm includes the main steps: converting from BGR color space to HSV color space, then, binary image is used to extract the marker area. Next, the Canny boundary detection technique is applied to determine the boundary of the markers in the container spreader. The center location of each marker is determined and used to calculate the distance from the camera system to the container spreader is calculated. The rope length accuracy by the image processing algorithm is 99,79%. It is satisfied for crane control purpose.

Deep Learning Techniques for Prediction, Detection, and Segmentation of Brain Tumors

2020 ◽  
pp. 118-154
Author(s):  
Prisilla Jayanthi ◽  
Muralikrishna Iyyanki
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Deep Learning ◽  
Brain Tumor ◽  
Color Space ◽  
Image Data ◽  
Semantic Segmentation ◽  
Training Image ◽  
Hsv Color Space ◽  
Learning Techniques

In deep learning, the main techniques of neural networks, namely artificial neural network, convolutional neural network, recurrent neural network, and deep neural networks, are found to be very effective for medical data analyses. In this chapter, application of the techniques, viz., ANN, CNN, DNN, for detection of tumors in numerical and image data of brain tumor is presented. First, the case of ANN application is discussed for the prediction of the brain tumor for which the disease symptoms data in numerical form is the input. ANN modelling was implemented for classification of human ethnicity. Next the detection of the tumors from images is discussed for which CNN and DNN techniques are implemented. Other techniques discussed in this study are HSV color space, watershed segmentation and morphological operation, fuzzy entropy level set, which are used for segmenting tumor in brain tumor images. The FCN-8 and FCN-16 models are used to produce a semantic segmentation on the various images. In general terms, the techniques of deep learning detected the tumors by training image dataset.

scholarly journals A New Contrast-Enhancing Feature for Cloud Detection in Ground-Based Sky Images

2015 ◽  
Vol 32 (2) ◽  
pp. 209-219 ◽  
Author(s):  
Vijai T. Jayadevan ◽  
Jeffrey J. Rodriguez ◽  
Alexander D. Cronin
Keyword(s):  
Imaging System ◽  
Color Image ◽  
Low Cost ◽  
Color Space ◽  
Cloud Detection ◽  
Hsv Color Space ◽  
Detection Algorithms ◽  
Camera Systems ◽  
New Feature ◽  
Thresholding Algorithm

AbstractFor this study a ground-based sky imaging system was developed that, unlike most other such systems, consists of a low-cost sun-tracking camera fitted with a fish-eye lens. The application of interest is short-term solar power forecasting, so cloud detection is an important step. The hybrid thresholding algorithm proposed by Li et al. for cloud detection is employed. Most cloud detection algorithms make use of the red and blue components in a color image. Though these features perform well for many images, they do not produce good results for the images in this study due to the insufficient contrast between cloud and sky pixels when using ratios between red and blue. To overcome this issue, a new feature, the normalized saturation/value (NSV) ratio, is proposed that is computed in the hue–saturation–value (HSV) color space. This study shows that the NSV ratio produces good contrast between cloud and sky pixels not only for the images in this study but also for general sky images acquired using different camera systems. The reasoning behind the choice of the new ratio is described, and quantitative and qualitative results are presented.

Pencarian File Gambar Berdasarkan Dominasi Warna

2011 ◽  
Vol 2 (1) ◽  
Author(s):  
Vina Chovan Epifania ◽  
Eko Sediyono
Keyword(s):  
Digital Image ◽  
Retrieval System ◽  
Color Image ◽  
Color Space ◽  
Image Data ◽  
Image Search ◽  
Test Results ◽  
Application Form ◽  
Space Model ◽  
Image File

Abstract. Image File Searching Based on Color Domination. One characteristic of an image that can be used in image searching process is the composition of the colors. Color is a trait that is easily seen by man in the picture. The use of color as a searching parameter can provide a solution in an easier searching for images stored in computer memory. Color images have RGB values that can be computed and converted into HSL color space model. Use of HSL images model is very easy because it can be calculated using a percent, so that in each pixel of the image can be grouped and named, this can give a dominant values of the colors contained in one image. By obtaining these values, the image search can be done quickly just by using these values to a retrieval system image file. This article discusses the use of the HSL color space model to facilitate the searching for a digital image in the digital image data warehouse. From the test results of the application form, a searching is faster by using the colors specified by the user. Obstacles encountered were still searching with a choice of 15 basic colors available, with a limit of 33% dominance of the color image search was not found. This is due to the dominant color in each image has the most dominant value below 33%.   Keywords: RGB, HSL, image searching Abstrak. Salah satu ciri gambar yang dapat dipergunakan dalam proses pencarian gambar adalah komposisi warna. Warna adalah ciri yang mudah dilihat oleh manusia dalam citra gambar. Penggunaan warna sebagai parameter pencarian dapat memberikan solusi dalam memudahkan pencarian gambar yang tersimpan dalam memori komputer. Warna gambar memiliki nilai RGB yang dapat dihitung dan dikonversi ke dalam model HSL color space. Penggunaan model gambar HSL sangat mudah karena dapat dihitung dengan menggunakan persen, sehingga dalam setiap piksel gambar dapat dikelompokan dan diberi nama, hal ini dapat memberikan suatu nilai dominan dari warna yang terdapat dalam satu gambar. Dengan diperolehnya nilai tersebut, pencarian gambar dapat dilakukan dengan cepat hanya dengan menggunakan nilai tersebut pada sistem pencarian file gambar. Artikel ini membahas tentang penggunaan model HSL color space untuk mempermudah pencarian suatu gambar digital didalam gudang data gambar digital. Dari hasil uji aplikasi yang sudah dibuat, diperoleh pencarian yang lebih cepat dengan menggunakan pilihan warna yang ditentukan sendiri oleh pengguna. Kendala yang masih dijumpai adalah pencarian dengan pilihan 15 warna dasar yang tersedia, dengan batas dominasi warna 33% tidak ditemukan gambar yang dicari. Hal ini disebabkan warna dominan disetiap gambar kebanyakan memiliki nilai dominan di bawah 33%. Kata Kunci: RGB, HSL, pencarian gambar

HSV color space based pupil position locating method

2014 ◽  
Author(s):  
Peng Cao ◽  
Qijie Zhao ◽  
Dawei Tu ◽  
Hui Shao
Keyword(s):  
Color Space ◽  
Hsv Color Space

State of hormonal regulation in experimental animals exposed to noise and vibration

2020 ◽  
pp. 680-681
Author(s):  
A. V. Lizarev ◽  
V. A. Pankov
Keyword(s):  
Blood Plasma ◽  
Hormonal Regulation ◽  
Adrenocorticotropic Hormone ◽  
Vibration Exposure ◽  
Noise And Vibration ◽  
Experimental Animals ◽  
In Blood Plasma

When exposed to noise and vibration in experimental animals there was a decrease in the content of threeiodinethyronine, thyroxin and adrenocorticotropic hormone in blood plasma after 15 and 30 days of experience. An increase in loads led to an increase in the level of threeiodinethyronine and thyroxin under vibration exposure and was normalized with noise. The content of adrenocorticotropic hormone leveled in both cases.

FOREGROUND IMAGE EXTRCTION IN THE HSV COLOR SPACE

2010 ◽  
Vol 7 (7) ◽  
pp. 1-4
Author(s):  
Jyh-Yeong Chang ◽  
Jia-Jye Shyu ◽  
Yi-Cheng Luo
Keyword(s):  
Color Space ◽  
Hsv Color Space
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