Conferences related to Microarrays And Lab-on-a-chip

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2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2020 IEEE 23rd International Conference on Information Fusion (FUSION)

The International Conference on Information Fusion is the premier forum for interchange of the latest research in data and information fusion, and its impacts on our society. The conference brings together researchers and practitioners from academia and industry to report on the latest scientific and technical advances.


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


2020 IEEE International Electron Devices Meeting (IEDM)

the IEEE/IEDM has been the world's main forum for reporting breakthroughs in technology, design, manufacturing, physics and the modeling of semiconductors and other electronic devices. Topics range from deep submicron CMOS transistors and memories to novel displays and imagers, from compound semiconductor materials to nanotechnology devices and architectures, from micromachined devices to smart -power technologies, etc.


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Periodicals related to Microarrays And Lab-on-a-chip

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Biomedical Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Computational Biology and Bioinformatics, IEEE/ACM Transactions on

Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...


Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on

Methods, algorithms, and human-machine interfaces for physical and logical design, including: planning, synthesis, partitioning, modeling, simulation, layout, verification, testing, and documentation of integrated-circuit and systems designs of all complexities. Practical applications of aids resulting in producible analog, digital, optical, or microwave integrated circuits are emphasized.


Magnetics, IEEE Transactions on

Science and technology related to the basic physics and engineering of magnetism, magnetic materials, applied magnetics, magnetic devices, and magnetic data storage. The Transactions publishes scholarly articles of archival value as well as tutorial expositions and critical reviews of classical subjects and topics of current interest.


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Most published Xplore authors for Microarrays And Lab-on-a-chip

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Xplore Articles related to Microarrays And Lab-on-a-chip

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Lab-on-a-chip particles manipulation for point-of-care diagnostic systems utilizing dielectrophoresis

2014 IEEE Conference on Biomedical Engineering and Sciences (IECBES), 2014

Particle manipulation has attracted the attention of many researchers around the globe for various biomedical applications. Although several methods have been utilized to sort particles on lab-on-a-chip platforms, dielectrophoresis (DEP) possess exclusive advantages over other methods. In this paper, we investigated microarray dot electrodes to manipulate microparticles. The geometry of the dot electrode enjoys unique benefits compared to other geometries, ...


Performance characterization of a low-cost dual-channel camera-based microarray scanner

2016 24th Iranian Conference on Electrical Engineering (ICEE), 2016

In this paper, we have proposed, designed, implemented, and characterized a low-cost camera-based microarray scanner which is capable of imaging fluorescently-labeled DNA or Protein microarrays. The proposed system is designed to simultaneously measure two different fluorescent dyes using two parallel channels which increase the overall scan speed. We have shown that the wide dynamic range of system makes it able ...


Segmentation of cDNA Microarray Spots Using K-means Clustering Algorithm and Mathematical Morphology

2009 WASE International Conference on Information Engineering, 2009

Complementary DNA microarray technology is a powerful tool in many areas. Usually a two channel microarray red-green (RG) image is obtained. Due to the nature of cDNA microarray technology, a number of impairments affect the cDNA microarray image before the analysis such as identification of differentially expressed genes. Microarray image processing plays a crucial role in the extraction and quantitative ...


On-Chip Biomedical Imaging

IEEE Reviews in Biomedical Engineering, 2013

Lab-on-a-chip systems have been rapidly emerging to pave the way toward ultra- compact, efficient, mass producible and cost-effective biomedical research and diagnostic tools. Although such microfluidic and microelectromechanical systems have achieved high levels of integration, and are capable of performing various important tasks on the same chip, such as cell culturing, sorting and staining, they still rely on conventional microscopes ...


cDNA microarray image processing using mathematical morphological segmentation

Proceedings of the 29th Chinese Control Conference, 2010

cDNA microarray is one of the most recent and important technology for exploring the genome. cDNA microarray image analysis aims to measure the intensity for each spot in the scanned image and this intensity represents the amount of a specific gene in the studied cell. It can affect subsequent analysis such as identification of differentially expressed genes. Microarray image analysis ...


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Educational Resources on Microarrays And Lab-on-a-chip

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IEEE-USA E-Books

  • Lab-on-a-chip particles manipulation for point-of-care diagnostic systems utilizing dielectrophoresis

    Particle manipulation has attracted the attention of many researchers around the globe for various biomedical applications. Although several methods have been utilized to sort particles on lab-on-a-chip platforms, dielectrophoresis (DEP) possess exclusive advantages over other methods. In this paper, we investigated microarray dot electrodes to manipulate microparticles. The geometry of the dot electrode enjoys unique benefits compared to other geometries, including enclosed areas of analysis and strong electric field with axisymmetrical distribution. DEP experiments were conducted to manipulate 1 μm polystyrene particles using the developed DEP system. Results showed that the response of the microparticle populations can be controlled by merely adjusting the applied frequency to induce either positive or negative DEP effects. In negative DEP case, microparticles were gathered at the dot center, while microparticles were collected at the dot edge in the case of positive DEP. Such microarray dot platforms can be utilized to develop economical point-of-care (POC) diagnostic systems by analyzing the transmitted light variations inside the dot regions.

  • Performance characterization of a low-cost dual-channel camera-based microarray scanner

    In this paper, we have proposed, designed, implemented, and characterized a low-cost camera-based microarray scanner which is capable of imaging fluorescently-labeled DNA or Protein microarrays. The proposed system is designed to simultaneously measure two different fluorescent dyes using two parallel channels which increase the overall scan speed. We have shown that the wide dynamic range of system makes it able to detect fluorophore densities from 100-106molecule/μm2. In each capture, a 5.6 mm × 3.7 mm field is imaged on a 22.3 mm × 14.9 mm (18 megapixels) CMOS sensor. Therefore, the microarray can be scanned with ~ 1μm2spatial resolution which is high enough to distinguish borders of spots with less than 50μm diameter. To characterize the scanner performance, we have used molecules labeled with fluorescent cyanine dyes, including Cy3 and Cy5; however, the proposed scanner can be modified to detect any other fluorescent dye with emission spectra within 400-800 nm. We believe it is the most cost-efficient microarray scanner ever achieved.

  • Segmentation of cDNA Microarray Spots Using K-means Clustering Algorithm and Mathematical Morphology

    Complementary DNA microarray technology is a powerful tool in many areas. Usually a two channel microarray red-green (RG) image is obtained. Due to the nature of cDNA microarray technology, a number of impairments affect the cDNA microarray image before the analysis such as identification of differentially expressed genes. Microarray image processing plays a crucial role in the extraction and quantitative analysis of the relative abundance of the DNA product. In this paper, a method combined K-means clustering algorithm and mathematical morphology is presented. Mathematical morphology is a useful tool for extracting image components. K-means clustering algorithm has a good performance in the segmentation of microarray image processing. The result of the experiment shows that the method presented in this paper is accurate, automatic and robust.

  • On-Chip Biomedical Imaging

    Lab-on-a-chip systems have been rapidly emerging to pave the way toward ultra- compact, efficient, mass producible and cost-effective biomedical research and diagnostic tools. Although such microfluidic and microelectromechanical systems have achieved high levels of integration, and are capable of performing various important tasks on the same chip, such as cell culturing, sorting and staining, they still rely on conventional microscopes for their imaging needs. Recently, several alternative on-chip optical imaging techniques have been introduced, which have the potential to substitute conventional microscopes for various lab-on-a-chip applications. Here we present a critical review of these recently emerging on-chip biomedical imaging modalities, including contact shadow imaging, lens-free holographic microscopy, fluorescent on-chip microscopy and lens-free optical tomography.

  • cDNA microarray image processing using mathematical morphological segmentation

    cDNA microarray is one of the most recent and important technology for exploring the genome. cDNA microarray image analysis aims to measure the intensity for each spot in the scanned image and this intensity represents the amount of a specific gene in the studied cell. It can affect subsequent analysis such as identification of differentially expressed genes. Microarray image analysis includes three tasks: spot gridding, segmentation and information extraction. This paper presents a new algorithm that achieves an automated way for applying mathematical morphology and morphological segmentation. It compares experimental results with those obtained from the widely used software GenePixPro (USA), Angulo J (France) and Hongwei Li (China). The result of experiment shows that it is robustness and precision. The way is adaptive to different shape, conglutination and deviant spot image.

  • A study on microarray image gridding techniques for DNA analysis

    Microarray is one of the most promising tools available for researchers in the life sciences to study gene expression profiles. Through microarray analysis, gene expression levels can be obtained, and the biological information of a disease can be identified. The gene expression information embedded in the microarray is extracted using image-processing techniques. Gridding is one of the important processes used to extract features in DNA microarray, by assigning each spot in the microarray with individual coordinates for further data interpretation. This paper evaluates popular techniques of DNA microarray image gridding in the literature with an emphasis on gridding accuracy, speed, and the ability to remove noise. Based on our evaluation, the Otsu method can provide a better performance in terms of processing speed, accuracy, and ability to remove noise compared to other methods discussed in this paper.

  • An improved SVM method for cDNA microarray image segmentation

    Microarray technology, as a revolutionary tool for biomedical research, has been widely used to analyze the gene expression level. Image segmentation is an important step of microarray technology. In this paper, we have presented an improved SVM method, which combined the SVM with the canny algorithm, the morphological algorithm and the fixed circle method, to obtain a better segmentation result. In addition, the initial image was preprocessed by using the image contrast enhancement and median filtering. Intensive experiments on the Stanford Microarray Database (SMD) and the Gene Expression Omnibus (GEO) database indicate that the proposed method is superior to the K-means method and the GenePix.Pro.

  • A Cost-Efficient Design for Microarray Image System

    Image based Microarray processing has been widely applied to the biotechnology field for identifying SNP variations. In order to reduce the cost for manufacturers, a flexible design for handling different layouts of containers and different numbers of spots is necessary to accomplish the need for different throughputs on the same microarray instrument. The key to making the microarray technology successful is spot recognition during the image processing. There are many factors that could affect the quality and alignment of spots. Both high accuracy and automation in spot intensity acquisition is required to have a correct result. Here, we present a cost-efficient design that will accommodate for different spot layouts with minimal required information.

  • Detection of Magnetically Labelled Microcarriers for Suspension Based Bioassay Technologies

    Microarrays and suspension-based assay technologies have attracted significant interest over the past decade with applications ranging from medical diagnostics to high throughput molecular biology. The throughput and sensitivity of a microarray will always be limited by the array density and slow reaction kinetics. Suspension (or bead) based technologies offer a conceptually different approach, improving detection by substituting a fixed plane of operation with millions of microcarriers. However, these technologies are currently limited by the number of unique labels that can be generated in order to identify the molecular probes on the surface. We have proposed a novel suspension-based technology that utilizes patterned magnetic films for the purpose of generating a writable label. The microcarriers consist of an SU-8 substrate that can be functionalized with various chemical or biological probes and magnetic elements, which are individually addressable by a magnetic sensor. The magnetization of each element is aligned in one of two stable directions, thereby acting as a magnetic bit. In order to detect the stray field and identify the magnetic labels, we have developed a microfluidic device with an integrated tunneling magnetoresistive (TMR) sensor, sourced from Micro Magnetics Inc. We present the TMR embedding architecture as well as detection results demonstrating the feasibility of magnetic labeling for lab- on-a-chip applications.

  • Software profiling analysis for DNA microarray image processing algorithm

    Microarray analysis is one of the most suitable tools available for scientists concerned with DNA sequences to study and examine gene expression. Through microarray analysis, the gene expression sequence can be obtained and biological information on many diseases can be acquired. The gene expression information contained in the microarray can be extracted using image- processing techniques. Microarray image processing consists of three main steps: gridding, segmentation and intensity extraction. This paper analyses the computational time for this microarray image processing. The results show that the intensity extraction consumes majority of the overall computational time. More detail analysis reveals that this high computational time is due to the background correction part of the process, as discussed in the second part of this paper.



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