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FSL-based Hardware Implementation for Parallel Computation of cDNA Microarray Image Segmentation

Bogdan Bot, Simina Emerich, Sorin Martoiu, Bogdan Belean
2015 International Journal of Advanced Computer Science and Applications  
The present paper proposes a FPGA based hardware implementations for microarray image processing algorithms in order eliminate the shortcomings of the existing software platforms: user intervention, increased computation time and cost. The proposed image processing algorithms exclude user intervention from processing. An application-specific architecture is designed aiming microarray image processing algorithms parallelization in order to speed up computation. Hardware architectures for
more » ... m based image enhancement, profile computation and image segmentation are described. The methodology to integrate the hardware architecture within a microprocessor system is detailed. The Fast Simplex Link (FSL) bus is used to connect the hardware architecture as speed up coprocessor of the microarray image processing system. Timing considerations were presented considering the levels of parallelism that can be achieved by using our proposed hardware architectures. The FPGA technology was chosen for implementation, due to its parallel computation capabilities and ease of reconfiguration.
doi:10.14569/ijacsa.2015.060704 fatcat:5nkljcq3qrablhgfnm3mcqcflu

Grid based high performance computing in satellite imagery. Case study - Perona-Malik filter
Сеточные высокопроизводительные вычисления в получении спутниковых изображний на примере фильтра Перона-Малик

Bogdan Belean, Carmen Belean, Calin Gabriel Floare, Codruta Mihaela Varodi, Adrian Bot, Gheorghe Adam
2015 Компьютерные исследования и моделирование  
Adam ____________________ КОМПЬЮТЕРНЫЕ ИССЛЕДОВАНИЯ И МОДЕЛИРОВАНИЕ ____________________ 402 © 2014 Bogdan Belean, Carmen Belean, Calin Gabriel Floare, Codruta Mihaela Varodi, Adrian Bot, Gheorghe  ...  Belean, C. Belean, C. Floare, C. Varodi, A. Bot, Gh.  ... 
doi:10.20537/2076-7633-2015-7-3-399-406 fatcat:723s7ahfarce5kv7qjo6av6paq

Biometrics Recognition based on Image Local Features Ordinal Encoding

Simina Emerich, Bogdan Belean
2017 International Journal of Advanced Computer Science and Applications  
In the present informational era, with the continue extension of embedded computing systems, the demand of faster and robust image descriptors is an important issue. However, image representation and recognition is an open problem. The aim of the paper is to embrace ordinal measurements for image analysis and to apply the concept for a real problem, such as biometric identification. Biometrics provides a robust solution for the identity management process and is increasingly more present in our
more » ... life. To explore the textural discriminative information of images, the paper proposes a new feature extraction technique, namely, Image Local Features Ordinal Encoding.
doi:10.14569/ijacsa.2017.081242 fatcat:lmnldu4ainexpidspoxtjew3ju

Unsupervised image segmentation for microarray spots with irregular contours and inner holes

Bogdan Belean, Monica Borda, Jörg Ackermann, Ina Koch, Ovidiu Balacescu
2015 BMC Bioinformatics  
Microarray analysis represents a powerful way to test scientific hypotheses on the functionality of cells. The measurements consider the whole genome, and the large number of generated data requires sophisticated analysis. To date, no gold-standard for the analysis of microarray images has been established. Due to the lack of a standard approach there is a strong need to identify new processing algorithms. Methods: We propose a novel approach based on hyperbolic partial differential equations
more » ... DEs) for unsupervised spot segmentation. Prior to segmentation, morphological operations were applied for the identification of co-localized groups of spots. A grid alignment was performed to determine the borderlines between rows and columns of spots. PDEs were applied to detect the inflection points within each column and row; vertical and horizontal luminance profiles were evolved respectively. The inflection points of the profiles determined borderlines that confined a spot within adapted rectangular areas. A subsequent k-means clustering determined the pixels of each individual spot and its local background. Results: We evaluated the approach for a data set of microarray images taken from the Stanford Microarray Database (SMD). The data set is based on two studies on global gene expression profiles of Arabidopsis Thaliana. We computed values for spot intensity, regression ratio, and coefficient of determination. For spots with irregular contours and inner holes, we found intensity values that were significantly different from those determined by the GenePix Pro microarray analysis software. We determined the set of differentially expressed genes from our intensities and identified more activated genes than were predicted by the GenePix software. Conclusions: Our method represents a worthwhile alternative and complement to standard approaches used in industry and academy. We highlight the importance of our spot segmentation approach, which identified supplementary important genes, to better explains the molecular mechanisms that are activated in a defense responses to virus and pathogen infection.
doi:10.1186/s12859-015-0842-3 pmid:26698293 pmcid:PMC4690322 fatcat:nvc56a52erfp3hl2harhdt3qcm

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

2021 Studies in Informatics and Control  
., 2018; Belean et al., 2015) .  ...  The selection of the rectangular region for each spot using the method proposed in (Belean et al., 2020) is the first step in segmenting microarray spots using active contours.  ... 
doi:10.24846/v30i3y202110 fatcat:uiw3redwizdjzlhat7ajfmgugq

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

Bogdan Belean, Robert Gutt, Carmen Costea, Ovidiu Balacescu
2020 IEEE Access  
Microarray image processing leads to the characterization of gene expression levels simultaneously, for all cellular transcripts (mRNAs) in a single experiment. The calculation of expression levels for each microarray spot/gene is a crucial step to extract valuable information. By measuring the mRNA levels for the whole genome, the microarray experiments are capable to study functionality, pathological phenotype, and response of cells to a pharmaceutical treatment. The processing of the
more » ... e number of non-homogeneous data contained in microarray images is still a challenge. 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 compared with existing approaches for gene expression levels estimation. The set of quality measures used for evaluation include: regression ratios, intensity ratios, mean absolute error, coefficient of variation and fold change factor. We applied the proposed image processing pipeline to a set of microarray images and compared our results with the ones delivered by Genepix, using the aforementioned quality measures. The advantage of our proposed method is highlighted by a selection of up-regulated genes that had been identified exclusively by our approach. These genes prove to add valuable information regarding the biological mechanism activated as a response of Arabidopsis T to pathogen infection.
doi:10.1109/access.2020.3019844 fatcat:stopwx2o3nhsdmpo2wcki2djpe

Dorsal Hand Vein Pattern Analysis and Neural Networks for Biometric Authentication

Bogdan BELEAN, Mihaela STREZA, Septimiu CRISAN, Simina EMERICH
2017 Studies in Informatics and Control  
Belean, Mihaela Streza, Septimiu Crisan, Simina Emerich Table 1.  ...  Figure 6 . 6 Input palm image partitioning and x p feature computation Figure 7 . 7 ROC curve of the proposed authentication systems based on NNA (green line), respectively SPMA (blue line) Bogdan  ... 
doi:10.24846/v26i3y201706 fatcat:4wgxtoqhorhgrjwnnuxi3kz7by

Two way clustering of microarray data using a hybrid approach

Raul Malutan, Bogdan Belean, Pedro Gomez Vilda, Monica Borda
2011 2011 34th International Conference on Telecommunications and Signal Processing (TSP)  
Belean is with the Communications Department, Technical University of Cluj-Napoca, 26-28 George Baritiu St., 400027 Cluj-Napoca, Romania, (phone: 004-0264-401564; fax: 004-264-401575; e-mail: bogdan.belean  ... 
doi:10.1109/tsp.2011.6043698 dblp:conf/tsp/MalutanBVB11 fatcat:o5jtzflo3ndojp2ps2magxboxm

Extraction of Point-of-Interest in Multispectral Images for Face Recognition

Kossi Kuma KATAKPE, Lyes AKSAS, Diarra MAMADOU, Pierre GOUTON
2022 International Journal of Advanced Computer Science and Applications  
Moreover Bogdan BELEAN et al. [37] use CNN (Convolutional Neural Network) for images segmentation. VI.  ... 
doi:10.14569/ijacsa.2022.0130291 fatcat:lwsf7a7qsjcnrd37wvs7m7n2ku

Brain Tumor Segmentation and Classification from MRI Images using Improved FLICM Segmentation and SCA Weight Optimized Wavelet-ELM Model

Debendra Kumar Sahoo, Satyasis Mishra, Mihir Narayan Mohanty
2022 International Journal of Advanced Computer Science and Applications  
Bogdan et al. [29] proposed an edge-based active contour model (ACM) driven by cellular neural networks (CNNs) for the segmentation procedure. Javeria et al. B.  ...  Belean et al. [14] proposed a density-based spatial clustering procedure driven by a level-set approach for microarray spot segmentation and quality measures were obtained. Wenxiu et al.  ... 
doi:10.14569/ijacsa.2022.0130753 fatcat:zlnwrclgbvf4fp4hnt26eojzri