Search results for " image processing"
showing 10 items of 2323 documents
Automatic detection of hemangiomas using unsupervised segmentation of regions of interest
2016
In this paper we compare the performances of three automatic methods of identifying hemangioma regions in images: 1) unsupervised segmentation using the Otsu method, 2) Fuzzy C-means clustering (FCM) and 3) an improved region growing algorithm based on FCM (RG-FCM). For each image, the starting point of the algorithms is a rectangular region of interest (ROI) containing the hemangioma. For computing the performances of each method, the ROIs had been manually labeled in 2 classes: pixels of hemangioma and pixels of non-hemangioma. The computed scores are given separately for each image, as well as global performances across all ROIs for both classes. The best classification of non-hemangioma…
Deep learning network for exploiting positional information in nucleosome related sequences
2017
A nucleosome is a DNA-histone complex, wrapping about 150 pairs of double-stranded DNA. The role of nucleosomes is to pack the DNA into the nucleus of the Eukaryote cells to form the Chromatin. Nucleosome positioning genome wide play an important role in the regulation of cell type-specific gene activities. Several biological studies have shown sequence specificity of nucleosome presence, clearly underlined by the organization of precise nucleotides substrings. Taking into consideration such advances, the identification of nucleosomes on a genomic scale has been successfully performed by DNA sequence features representation and classical supervised classification methods such as Support Vec…
Deep Learning Architectures for DNA Sequence Classification
2017
DNA sequence classification is a key task in a generic computational framework for biomedical data analysis, and in recent years several machine learning technique have been adopted to successful accomplish with this task. Anyway, the main difficulty behind the problem remains the feature selection process. Sequences do not have explicit features, and the commonly used representations introduce the main drawback of the high dimensionality. For sure, machine learning method devoted to supervised classification tasks are strongly dependent on the feature extraction step, and in order to build a good representation it is necessary to recognize and measure meaningful details of the items to cla…
Three-dimensional multiple-particle tracking with nanometric precision over tunable axial ranges
2017
The precise localization of nanometric objects in three dimensions is essential to identify functional diffusion mechanisms in complex systems at the cellular or molecular level. However, most optical methods can achieve high temporal resolution and high localization precision only in two dimensions or over a limited axial (z) range. Here we develop a novel wide-field detection system based on an electrically tunable lens that can track multiple individual nanoscale emitters in three dimensions over a tunable axial range with nanometric localization precision. The optical principle of the technique is based on the simultaneous acquisition of two images with an extended depth of field while …
On the growth and form of cortical convolutions
2016
International audience; The rapid growth of the human cortex during development is accompanied by the folding of the brain into a highly convoluted structure1-3. Recent studies have focused on the genetic and cellular regulation of cortical growth4-8, but understanding the formation of the gyral and sulcal convolutions also requires consideration of the geometry and physical shaping of the growing brain9-15. To study this, we use magnetic resonance images to build a 3D-printed layered gel mimic of the developing smooth fetal brain; when immersed in a solvent, the outer layer swells relative to the core, mimicking cortical growth. This relative growth puts the outer layer into mechanical com…
New Approach of Controlling Cardiac Alternans
2018
The alternans of the cardiac action potential duration is a pathological rhythm. It is considered to be relating to the onset of ventricular fibrillation and sudden cardiac death. It is well known that, the predictive control is among the control methods that use the chaos to stabilize the unstable fixed point. Firstly, we show that alternans (or period-2 orbit) can be suppressed temporally by the predictive control of the periodic state of the system. Secondly, we determine an estimation of the size of a restricted attraction's basin of the unstable equilibrium point representing the unstable regular rhythm stabilized by the control. This result allows the application of predictive control…
Variance component analysis to assess protein quantification in biomarker discovery. Application to MALDI-TOF mass spectrometry.
2017
International audience; Controlling the technological variability on an analytical chain is critical for biomarker discovery. The sources of technological variability should be modeled, which calls for specific experimental design, signal processing, and statistical analysis. Furthermore, with unbalanced data, the various components of variability cannot be estimated with the sequential or adjusted sums of squares of usual software programs. We propose a novel approach to variance component analysis with application to the matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) technology and use this approach for protein quantification by a classical signal processing algori…
MSAProbs-MPI: parallel multiple sequence aligner for distributed-memory systems
2016
This is a pre-copyedited, author-produced version of an article accepted for publication in Bioinformatics following peer review. The version of recordJorge González-Domínguez, Yongchao Liu, Juan Touriño, Bertil Schmidt; MSAProbs-MPI: parallel multiple sequence aligner for distributed-memory systems, Bioinformatics, Volume 32, Issue 24, 15 December 2016, Pages 3826–3828, https://doi.org/10.1093/bioinformatics/btw558is available online at: https://doi.org/10.1093/bioinformatics/btw558 [Abstracts] MSAProbs is a state-of-the-art protein multiple sequence alignment tool based on hidden Markov models. It can achieve high alignment accuracy at the expense of relatively long runtimes for large-sca…
Ultra-Fast Detection of Higher-Order Epistatic Interactions on GPUs
2017
Detecting higher-order epistatic interactions in Genome-Wide Association Studies (GWAS) remains a challenging task in the fields of genetic epidemiology and computer science. A number of algorithms have recently been proposed for epistasis discovery. However, they suffer from a high computational cost since statistical measures have to be evaluated for each possible combination of markers. Hence, many algorithms use additional filtering stages discarding potentially non-interacting markers in order to reduce the overall number of combinations to be examined. Among others, Mutual Information Clustering (MIC) is a common pre-processing filter for grouping markers into partitions using K-Means…
Decentralised trust-management inspired by ant pheromones
2017
Computational trust is increasingly utilised to select interaction partners in open technical systems consisting of heterogeneous, autonomous agents. Current approaches rely on centralised elements for managing trust ratings (i.e. control and provide access to aggregated ratings). Consider a grid computing application as illustrating example: agents share their computing resources and cooperate in terms of processing computing jobs. These agents are free to join and leave, and they decide on their own with whom to interact. The impact of malicious or uncooperative agents can be countered by only cooperating with agents that have shown to be benevolent: trust relationships are established. T…