819 Hits in 3.6 sec

Active Contours Driven by Cellular Neural Networks for Image Segmentation in Biomedical Application

2021 Studies in Informatics and Control  
The novelty of this approach lies in the fact that this is a segmentation procedure which uses an edge-based active contour model (ACM) driven by cellular neural networks (CNNs).  ...  In case of microarray images, microarray spots represented as circular shapes are localised and used further on for the estimation of gene expression levels, based on the average pixel intensities.  ...  A selection of microarray spots is used for illustrating the visual results obtained by using the proposed active contour driven by CNN for spot segmentation (see Figure 4 ).  ... 
doi:10.24846/v30i3y202110 fatcat:uiw3redwizdjzlhat7ajfmgugq

Microarray spot partitioning by autonoumsly organising maps thorugh contour model

Karthik S. A., Manjunath S. S.
2020 International Journal of Electrical and Computer Engineering (IJECE)  
In this piece of writing, an innovative way for spot partitioning of microarray images using autonomously organizing maps (AOM) method through C-V model has been proposed.  ...  to decide whether to get smaller or get bigger of contour.  ...  Figure 1 . 1 Typical microarray spots Figure 2 . 2  Formulation of unsupervised active contour model  Guide for contour growth  Presents a well experimental work in terms of accuracy and robustness  ... 
doi:10.11591/ijece.v10i1.pp746-756 fatcat:vt4lcxceyzbetkkyj6fig327pq

Microarray image analysis: from image processing methods to gene expression levels estimation

Bogdan Belean, Robert Gutt, Carmen Costea, Ovidiu Balacescu
2020 IEEE Access  
We propose a density based spatial clustering procedure driven by a level-set approach for microarray spot segmentation together with a complete set of quality measures used to evaluate the proposed method  ...  The calculation of expression levels for each microarray spot/gene is a crucial step to extract valuable information.  ...  The resulted LSF is also represented for each microarray spot, showing its convergence towards the spot edge.  ... 
doi:10.1109/access.2020.3019844 fatcat:stopwx2o3nhsdmpo2wcki2djpe

A Fully Automated Method for Noisy cDNA Microarray Image Quantification

Islam A. Fouad, Mai S. Mabrouk, Amr A. Sharawy
A segmentation technique based on 'edge-detection' is applied to identify the spots and separate the foreground from the background is known as microarray image segmentation.  ...  for each spot on the microarray.  ...  The combination of Markov random field based grid segmentation and active contour modeling constitutes an approach suitable for spot detection and segmentation [7] .  ... 
doi:10.24297/ijct.v11i3.1170 fatcat:mcvp6cw6fbcknb7y4bzlld6ugi


Jesús Angulo
2011 Image Analysis and Stereology  
Robust image analysis of spots in microarrays (quality control + spot segmentation + quantification) is a requirement for automated software which is of fundamental importance for a high-throughput analysis  ...  of genomics microarray-based data.  ...  ACKNOWLEDGEMENTS The author gratefully thanks Fernand Meyer for his valuable suggestions. This work is part of the French Project GEMBIO-Bioinformatique 2003  ... 
doi:10.5566/ias.v27.p107-124 fatcat:qk2k6xgg55dobdn5epvw5e5ek4

Automatic Segmentation of cDNA Microarray Images Using Different Methods

Islam Fouad, Mai S. Mabrouk, Amr Sharawy
2014 Journal of Biomedical Engineering and Medical Imaging  
Thus, microarray data processing steps become critical for performing optimal microarray data analysis and deriving meaningful biological information from microarray images .Segmentation is the process  ...  The slide name is (shae082) and it is a cDNA microarrays spotted by a total of 24192 genes.  ...  The combination of Markov random field based grid segmentation and active contour modeling constitutes an approach suitable for spot detection and segmentation [7] .  ... 
doi:10.14738/jbemi.15.476 fatcat:kb64uokd45fkza4qtlgjqykbd4

An Overview of DNA Microarray Grid Alignment and Foreground Separation Approaches

Peter Bajcsy
2006 EURASIP Journal on Advances in Signal Processing  
Thus, understanding microarray data processing steps becomes critical for performing optimal microarray data analysis.  ...  This paper overviews DNA microarray grid alignment and foreground separation approaches.  ...  We will describe only those that have been frequently used with microarray images, such as seeded region growing, watershed segmentation, and active contour models.  ... 
doi:10.1155/asp/2006/80163 fatcat:ennacwyq5jdpvmfpuzep7a6vzy

A Combinational Clustering Based Method for cDNA Microarray Image Segmentation

Guifang Shao, Tiejun Li, Wangda Zuo, Shunxiang Wu, Tundong Liu, Shu-Dong Zhang
2015 PLoS ONE  
To improve the segmentation accuracy, in this article we present a combination clustering based segmentation approach that may be more reliable and able to segment spots automatically.  ...  Next, among each spot region, the moving k-means clustering is first conducted to separate the spot from background and then the k-means clustering algorithms are combined for those spots failing to obtain  ...  Acknowledgments The authors thank Yuhua Wen for his help in revising the manuscript and thank Xue Han for her help in preparing the experiments.  ... 
doi:10.1371/journal.pone.0133025 pmid:26241767 pmcid:PMC4524615 fatcat:pdnqqrixlnckbdnrusmkoxczxy

New methodology for microarray spot segmentation and gene expression analysis

A. Hudaib Amjad, N. Fakhouri Hussam, Ghnemat Rawan
2016 Scientific Research and Essays  
This paper proposes a new methodology to improve microarray spot analysis based on spot extracted segments.  ...  It concentrates on each spot segment area independently rather than analyzing all the spots area together of the microarray image.  ...  The adaptive shape segmentation segments a spots by its shape either by the seeded region growing (SRG) (Bariamis et al., 2010) or the globally optimal geodesic active contours (GOGAC) (Alhadidi et  ... 
doi:10.5897/sre2015.6378 fatcat:kekptuatlvcejnuvb4norgg7ty

Hybrid Spot Segmentation in Four-Channel Microarray Genotyping Image Data

Mohsen Abbaspour, Rafeef Abugharbieh, Mohua Podder, Ben Tripp, Scott Tebbutt
2006 2006 IEEE International Symposium on Signal Processing and Information Technology  
In this paper we present a novel hybrid algorithm for spot segmentation in four-channel genotyping microarray images.  ...  A new four-dimensional clustering approach for fullyautomated spot segmentation is proposed, along with a new iterative method to automatically identify the number of clusters in a single-spot area.  ...  Zamar for their continual support.  ... 
doi:10.1109/isspit.2006.270761 fatcat:wgugvbczxbbitfsb7dqfk6ov4e

Automatic Spot Identification Method for High Throughput Surface Plasmon Resonance Imaging Analysis

Zhiyou Wang, Xiaoqing Huang, Zhiqiang Cheng
2018 Biosensors  
An automatic spot identification method is developed for high throughput surface plasmon resonance imaging (SPRi) analysis.  ...  Results show that our method can locate spots in the microarray accurately regardless of the microarray pattern, spot-background contrast, light nonuniformity and spotting defects, but also can provide  ...  after image segmentation.  ... 
doi:10.3390/bios8030085 pmid:30217054 pmcid:PMC6163621 fatcat:jwhnn6lwcjeivabxmn26mbsfjm

Image Processing of Porous Silicon Microarray in Refractive Index Change Detection

Zhiqing Guo, Zhenhong Jia, Jie Yang, Nikola Kasabov, Chuanxi Li
2017 Sensors  
First, based on the characteristics of different components in HSV (Hue, Saturation, Value) space, a special pretreatment is proposed for the reflected light image to obtain the contour edges of the array  ...  The segmentation algorithm makes the dots in a regular arrangement, excludes the edges and the bright spots.  ...  Spot Segmentation In order to obtain the position of the target spots, spot segmentation is a key step in microarray image processing. It has great significance for subsequent image analysis.  ... 
doi:10.3390/s17061335 pmid:28594383 pmcid:PMC5492526 fatcat:to6lkps46bhjfbubschno6h3he

Fully-automated analysis of multi-resolution four-channel micro-array genotyping data

Mohsen Abbaspour, Rafeef Abugharbieh, Mohua Podder, Scott J. Tebbutt, Joseph M. Reinhardt, Josien P. W. Pluim
2006 Medical Imaging 2006: Image Processing  
However, fast, robust, and precise image processing tools are required for the prospective practical use of microarray-based genetic testing for predicting disease susceptibilities and drug effects in  ...  Fourchannel DNA microarray technology is a robust and accurate tool for determining genotypes of multiple genetic markers in individuals.  ...  Other reported approaches include the use of Active Contour Models 11 and the Wavelet Transform 12 , however, the reported results were still prone to errors due to noise.  ... 
doi:10.1117/12.650814 dblp:conf/miip/AbbaspourAPT06 fatcat:3ukgbii4vvgdpovjafmzqrrhla

Micro Array Images Segmentation Using a Novel Approach [chapter]

Pooria Jafari Moghadam Fard, M. H. Moradi
2009 International Federation for Medical and Biological Engineering Proceedings  
In the other hand, this paper describes image processing methods for automatic spotted microarray image analysis.  ...  Automatic gridding is important to achieve constant data quality and is, therefore, especially interesting for large-scale experiments as well as for integration of microarray expression data from different  ...  Jinn Ho and Wen-Liang Hwang [9] integrated the active contour (snake) model and the Fisher criterion to capture, respectively, the boundary and region information of microarray images.  ... 
doi:10.1007/978-3-642-03882-2_403 fatcat:pokt5ohsx5fbrpidrxtmogkubu

cDNA microarray image segmentation using root signals

Rastislav Lukac, Konstantinos N. Plataniotis
2006 International journal of imaging systems and technology (Print)  
A vector processing based framework suitable for cDNA microarray image segmentation is introduced and analyzed in this paper.  ...  The solution converges to a root signal that represents the segmented cDNA microarray image with the regular spots ideally separated from the background and with their coloration uniquely described by  ...  The combination of Markov random field based grid segmentation and active contour modeling constitutes an approach suitable for spot detection and segmentation (Katzer et al., 2003) .  ... 
doi:10.1002/ima.20067 fatcat:ijvcaowxszfkbccefflzrofk3y
« Previous Showing results 1 — 15 out of 819 results