scholarly journals Label-Free Biosensing Method for the Detection of a Pancreatic Cancer Biomarker Based on Dielectrophoresis Spectroscopy

Chemosensors ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 33 ◽  
Author(s):  
Fleming Dackson Gudagunti ◽  
Logeeshan Velmanickam ◽  
Dharmakeerthi Nawarathna ◽  
Ivan Lima
Keyword(s):  
Pancreatic Cancer ◽  
Early Stage ◽  
Mie Scattering ◽  
Processing Technique ◽  
Cancer Biomarker ◽  
Image Processing Technique ◽  
Label Free ◽  
Transduction Mechanism ◽  
Diagnosis And Prognosis ◽  
Cutoff Levels

We show that negative dielectrophoresis (DEP) spectroscopy is an effective transduction mechanism of a biosensor for the diagnosis and prognosis of pancreatic cancer using the biomarker CA 19-9. A substantial change in the negative DEP force applied to functionalized polystyrene microspheres (PM) was observed with respect to both the concentration level of the pancreatic cancer biomarker CA 19-9 and the frequency of the electric field produced by a pearl shaped interdigitated gold micro-electrode. The velocity of repulsion of a set of PM functionalized to a monoclonal antibody to CA 19-9 was calculated for several concentration cutoff levels of CA 19-9, including 0 U/mL and 37 U/mL, at the frequency range from 0.5 to 2 MHz. The velocity of repulsion of the PM from the electrode was determined using a side illumination and an automated software using a real-time image processing technique that captures the Mie scattering from the PM. Since negative DEP spectroscopy is an effective transduction mechanism for the detection of the cutoff levels of CA 19-9, it has the potential to be used in the early stage diagnosis and in the prognosis of pancreatic cancer.

scholarly journals Automatic Diagnosis of Glaucoma using Image Processing Technique

2019 ◽  
Vol 9 (2) ◽  
pp. 3984-3987
Keyword(s):  
Optic Nerve ◽  
Optic Disc ◽  
Vision Loss ◽  
Early Stage ◽  
Threshold Value ◽  
Processing Technique ◽  
Least Square ◽  
Disc Height ◽  
Image Processing Technique ◽  
Human Eye

Glaucoma is a human eye condition which will affect the optic nerve present in the retina. This condition occurs due to the abnormal ocular pressure in human eye. If it is not diagnosed and treated well in advance, it may lead to blindness. This is the major problem of elderly people all over the world. The best way to avoid vision loss due to glaucoma is to detect the disease at the early stage and treat it as soon as possible. These are the keys to prevent blindness. As vision is an important organ in human body it is advisable to keep it healthy. The optic cup in the retina will be pulled in towards the optic nerve away from the optic disc. At one point, the cup will be detached from the retina, causing blindness. So if one can monitor by measuring the optic disc to cup ratio, the progression of glaucoma can be diagnosed earlier. The proposed method detects the optic disc and cup using thresholding method. Direct least square fitting algorithm is used here to fit the ellipse in order to calculate the cup height and disc height. Then the ratio is calculated. If the calculated ratio is above the threshold value, it is considered as glaucoma affected eye otherwise not. The CDR is calculated using the formula VDH/VCH (Vertical Disc Height to the Vertical Cup Height). Thus, the proposed method helps to automatically detect the glaucoma disease with better sensitivity and specificity.

Early Stage Diagnosis of Eye Herpes (NAGIN) by Machine Learning and Image Processing Technique

2019 ◽  
Vol 10 (2) ◽  
pp. 27-36
Author(s):  
Kakasaheb Rangnarh Nikam
Keyword(s):  
Early Stage ◽  
Processing Technique ◽  
The Body ◽  
Image Processing Technique ◽  
Eye Disease ◽  
Front Part ◽  
Eye Detection ◽  
Herpes Keratitis ◽  
Simplex Virus

Eyes are very important parts of the body. Automatic eye detection is must to diagnose various eye disease including Herpes (Nagin) in early stages. Type 1 Herpes Simplex Virus (HSV) may damaging the eye and causing permanent eyesight problems. Herpes keratitis, commonly known as eye herpes, is an inflammation of the cornea, the clear dome that covers the front part of the eye. The proposed method potentially reduce workload on eye doctors and increase the efficiency of limited healthcare resources.

scholarly journals Highly sensitive and portable mRNA detection platform for early cancer detection

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Hongxia Li ◽  
Antony R. Warden ◽  
Wenqiong Su ◽  
Jie He ◽  
Xiao Zhi ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Cells ◽  
Early Stage ◽  
Point Of Care ◽  
Cancer Biomarker ◽  
Detection Sensitivity ◽  
Detection Methods ◽  
Mrna Detection ◽  
Amplification Method ◽  
Pancreatic Cancer Cells

AbstractPancreatic cancer, at unresectable advanced stages, presents poor prognoses, which could be prevented by early pancreatic cancer diagnosis methods. Recently, a promising early-stage pancreatic cancer biomarker, extracellular vesicles (EVs) related glypican-1 (GPC1) mRNA, is found to overexpress in pancreatic cancer cells. Current mRNA detection methods usually require expensive machinery, strict preservation environments, and time-consuming processes to guarantee detection sensitivity, specificity, and stability. Herein, we propose a novel two-step amplification method (CHAGE) via the target triggered Catalytic Hairpin Assembly strategy combined with Gold-Enhanced point-of-care-testing (POCT) technology for sensitive visual detection of pancreatic cancer biomarker. First, utilizing the catalyzed hairpin DNA circuit, low expression of the GPC1 mRNA was changed into amplification product 1 (AP1, a DNA duplex) as the next detection targets of the paper strips. Second, the AP1 was loaded onto a lateral flow assay and captured with the gold signal nanoparticles to visualize results. Finally, the detected results can be further enhanced by depositing gold to re-enlarge the sizes of gold nanoparticles in detection zones. As a result, the CHAGE methodology lowers the detection limit of mRNA to 100 fM and provides results within 2 h at 37 °C. Furthermore, we demonstrate the successful application in discriminating pancreatic cancer cells by analyzing EVs’ GPC1 mRNA expression levels. Hence, the CHAGE methodology proposed here provides a rapid and convenient POCT platform for sensitive detection of mRNAs through unique probes designs (COVID, HPV, etc.).

scholarly journals Turbulent thermal diffusion of aerosols in geophysics and in laboratory experiments

2004 ◽  
Vol 11 (3) ◽  
pp. 343-350 ◽  
Author(s):  
A. Eidelman ◽  
T. Elperin ◽  
N. Kleeorin ◽  
A. Krein ◽  
I. Rogachevskii ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Thermal Diffusion ◽  
Large Scale ◽  
Laboratory Experiments ◽  
Turbulent Transport ◽  
Mie Scattering ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Mean Temperature ◽  
Image Velocimetry

Abstract. We discuss a new phenomenon of turbulent thermal diffusion associated with turbulent transport of aerosols in the atmosphere and in laboratory experiments. The essence of this phenomenon is the appearance of a nondiffusive mean flux of particles in the direction of the mean heat flux, which results in the formation of large-scale inhomogeneities in the spatial distribution of aerosols that accumulate in regions of minimum mean temperature of the surrounding fluid. This effect of turbulent thermal diffusion was detected experimentally. In experiments turbulence was generated by two oscillating grids in two directions of the imposed vertical mean temperature gradient. We used Particle Image Velocimetry to determine the turbulent velocity field, and an Image Processing Technique based on an analysis of the intensity of Mie scattering to determine the spatial distribution of aerosols. Analysis of the intensity of laser light Mie scattering by aerosols showed that aerosols accumulate in the vicinity of the minimum mean temperature due to the effect of turbulent thermal diffusion.

scholarly journals Smart Leaf Recognition System

2020 ◽  
Vol 9 (5) ◽  
pp. 289-291
Keyword(s):  
Image Processing ◽  
Early Stage ◽  
Recognition System ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Plant Leaves ◽  
Plant Leaf ◽  
Automatic Technique

One of major issue nowadays is the agricultural productivity which is something our Nation’s economy highly depends. Technology based advancements may lead to detection of diseases in plants which are quite natural. Care should be taken in this area before it causes serious effects on plants which mainly affect the product quality, quantity or productivity. Early stage detection of diseases in plants through some automatic technique is beneficial as it reduces a huge work of monitoring in large acres of crops. When they appear on plant leaves, earlier detection helps us to increase the yield and productivity. This paper presents an algorithm for image processing technique which is used for automatic detection and classification of plant leaf diseases with the help of raspberry pi and sensors. This survey is about different diseases and its classification, techniques which are used for plant leaf disease detection and also its respective fertilizer sprayed on the leaves.

scholarly journals Prediction and Analysis of Paddy Crops Disease in Artificial Intelligence Techniques

2021 ◽  
pp. 261-268
Author(s):  
Tanmayee Tushar Parbat ◽  
Rohan Benhal ◽  
Honey Jain ◽  
Dr. Vinayak Musale
Keyword(s):  
Image Processing ◽  
Early Stage ◽  
Processing Technique ◽  
Plant Diseases ◽  
Image Processing Technique ◽  
Human Beings ◽  
Yield Level ◽  
Disease Occurrence ◽  
Causative Agents ◽  
Paddy Crop

The survival of human beings is generally based on the proper productivity of agriculture. The paddy plant is considered as a major planting crop in improving the economical level of our country. Nowadays, the yield level of paddy crop might be minimized due to several diseases. Bacteria, fungi, virus and certain harmful insects are the main causative agents for such disease occurrence on the paddy crop. The diseases which affect the early stage of the paddy crops influences in the whole stage of crop cultivation. In early days of agriculture, the manual detection of diseases has been carried out by farmers. Image processing is one of the emerging techniques for identifying and classifying the different types of diseases and it overcomes the issues encountered during the manual detection of diseases. Image processing technique solves several issues involved in the cultivation of crops including, recognition and classification of plant diseases, discrimination of certain weeds and disease forecasting.

A New Image Processing Technique for STEM

1974 ◽  
Vol 32 ◽  
pp. 432-433
Author(s):  
Yasushi Kokubo ◽  
Hirotami Koike ◽  
Teruo Someya
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Scanning Electron Microscopy ◽  
Elastic Scattering ◽  
Field Emission ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Energy Analyzer ◽  
Scanning Microscope ◽  
Scanning Electron

One of the advantages of scanning electron microscopy is the capability for processing the image contrast, i.e., the image processing technique. Crewe et al were the first to apply this technique to a field emission scanning microscope and show images of individual atoms. They obtained a contrast which depended exclusively on the atomic numbers of specimen elements (Zcontrast), by displaying the images treated with the intensity ratio of elastically scattered to inelastically scattered electrons. The elastic scattering electrons were extracted by a solid detector and inelastic scattering electrons by an energy analyzer. We noted, however, that there is a possibility of the same contrast being obtained only by using an annular-type solid detector consisting of multiple concentric detector elements.

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

An Enhanced Technique for Classification of Fruits using Shape Color and Texture Features

2017 ◽  
Vol 7 (7) ◽  
pp. 408
Author(s):  
Yashpal Jitarwal ◽  
Tabrej Ahamad Khan ◽  
Pawan Mangal
Keyword(s):  
Image Processing ◽  
Texture Features ◽  
Automatic Classification ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Advance Technique ◽  
Time Required ◽  
Fruit Sorting ◽  
Human Inspection

In earlier times fruits were sorted manually and it was very time consuming and laborious task. Human sorted the fruits of the basis of shape, size and color. Time taken by human to sort the fruits is very large therefore to reduce the time and to increase the accuracy, an automatic classification of fruits comes into existence.To improve this human inspection and reduce time required for fruit sorting an advance technique is developed that accepts information about fruits from their images, and is called as Image Processing Technique.

Sign in / Sign up

Export Citation Format

Share Document