The approach of using more than one processor to compute in order to overcome the complexity of different medical imaging methods that make up an overall job is known as GPU (graphic processing unit)-based parallel processing. It is extremely important for several medical imaging techniques such as image classification, object detection, image segmentation, registration, and content-based image retrieval, since the GPU-based parallel processing approach allows for time-efficient computation by a software, allowing multiple computations to be completed at once. On the other hand, a non-invasive imaging technology that may depict the shape of an anatomy and the biological advancements of the human body is known as magnetic resonance imaging (MRI). Implementing GPU-based parallel processing approaches in brain MRI analysis with medical imaging techniques might be helpful in achieving immediate and timely image capture. Therefore, this extended review (the extension of the IWBBIO2023 conference paper) offers a thorough overview of the literature with an emphasis on the expanding use of GPU-based parallel processing methods for the medical analysis of brain MRIs with the imaging techniques mentioned above, given the need for quicker computation to acquire early and real-time feedback in medicine. Between 2019 and 2023, we examined the articles in the literature matrix that include the tasks, techniques, MRI sequences, and processing results. As a result, the methods discussed in this review demonstrate the advancements achieved until now in minimizing computing runtime as well as the obstacles and problems still to be solved in the future.
- Keywords
- GPU, MRI, parallel processing, review,
- MeSH
- Algorithms * MeSH
- Humans MeSH
- Magnetic Resonance Imaging methods MeSH
- Brain MeSH
- Computer Graphics * MeSH
- Image Processing, Computer-Assisted methods MeSH
- Software MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Detached off-grids, subject to the generated renewable energy (RE), need to balance and compensate the unstable power supply dependent on local source potential. Power quality (PQ) is a set of EU standards that state acceptable deviations in the parameters of electrical power systems to guarantee their operability without dropout. Optimization of the estimated PQ parameters in a day-horizon is essential in the operational planning of autonomous smart grids, which accommodate the norms for the specific equipment and user demands to avoid malfunctions. PQ data for all system states are not available for dozens of connected / switched on household appliances, defined by their binary load series only, as the number of combinations grows exponentially. The load characteristics and eventual RE contingent supply can result in system instability and unacceptable PQ events. Models, evolved by Artificial Intelligence (AI) methods using self-optimization algorithms, can estimate unknown cases and states in autonomous systems contingent on self-supply of RE power related to chaotic and intermitted local weather sources. A new multilevel extension procedure designed to incrementally improve the applicability and adaptability to training data. The initial AI model starts with binary load series only, which are insufficient to represent complex data patterns. The input vector is progressively extended with correlated PQ parameters at the next estimation level to better represent the active demand of the power consumer. Historical data sets comprise training samples for all PQ parameters, but only the load sequences of the switch-on appliances are available in the next estimation states. The most valuable PQ parameters are selected and estimated in the previous algorithm stages to be used as supplementary series in the next more precise computing. More complex models, using the previous PQ-data approximates, are formed at the secondary processing levels to estimate the target PQ-output in better quality. The new added input parameters allow us to evolve a more convenient model form. The proposed multilevel refinement algorithm can be generally applied in modelling of unknown sequence states of dynamical systems, initially described by binary series or other insufficient limited-data variables, which are inadequate in a problem representation. Most AI computing techniques can adapt this strategy to improve their adaptive learning and model performance.
BACKGROUND: Next generation sequencing (NGS) technology allows laboratories to investigate virome composition in clinical and environmental samples in a culture-independent way. There is a need for bioinformatic tools capable of parallel processing of virome sequencing data by exactly identical methods: this is especially important in studies of multifactorial diseases, or in parallel comparison of laboratory protocols. RESULTS: We have developed a web-based application allowing direct upload of sequences from multiple virome samples using custom parameters. The samples are then processed in parallel using an identical protocol, and can be easily reanalyzed. The pipeline performs de-novo assembly, taxonomic classification of viruses as well as sample analyses based on user-defined grouping categories. Tables of virus abundance are produced from cross-validation by remapping the sequencing reads to a union of all observed reference viruses. In addition, read sets and reports are created after processing unmapped reads against known human and bacterial ribosome references. Secured interactive results are dynamically plotted with population and diversity charts, clustered heatmaps and a sortable and searchable abundance table. CONCLUSIONS: The Vipie web application is a unique tool for multi-sample metagenomic analysis of viral data, producing searchable hits tables, interactive population maps, alpha diversity measures and clustered heatmaps that are grouped in applicable custom sample categories. Known references such as human genome and bacterial ribosomal genes are optionally removed from unmapped ('dark matter') reads. Secured results are accessible and shareable on modern browsers. Vipie is a freely available web-based tool whose code is open source.
- Keywords
- Assembly, Metagenomics, NGS analysis, Parallel processing, Viral dark matter, Viromes, Virus, Visualization,
- MeSH
- Genetic Variation MeSH
- Genomics methods MeSH
- Internet * MeSH
- Humans MeSH
- Microbiota genetics MeSH
- Software * MeSH
- Viruses genetics MeSH
- High-Throughput Nucleotide Sequencing * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The paper describes a novel control strategy for simultaneous manipulation of several microscale particles over a planar microelectrode array using dielectrophoresis. The approach is based on a combination of numerical nonlinear optimization, which gives a systematic computational procedure for finding the voltages applied to the individual electrodes, and exploitation of the intrinsic noise, which compensates for the loss of controllability when two identical particles are exposed to identical forces. Although interesting on its own, the proposed functionality can also be seen as a preliminary achievement in a quest for a technique for separation of two particles. The approach is tested experimentally with polystyrene beads (50 microns in diameter) immersed in deionized water on a flat microelectrode array with parallel electrodes. A digital camera and computer vision algorithm are used to measure the positions. Two distinguishing features of the proposed control strategy are that the range of motion is not limited to interelectrode gaps and that independent manipulation of several particles simultaneously is feasible even on a simple microelectrode array.
- Keywords
- Dielectrophoresis, Feedback control, Micromanipulation, Parallel manipulation, Visual feedback,
- MeSH
- Algorithms MeSH
- Equipment Design MeSH
- Electrodes MeSH
- Electrophoresis methods MeSH
- Noise MeSH
- Micromanipulation instrumentation methods MeSH
- Microspheres MeSH
- Signal Processing, Computer-Assisted instrumentation MeSH
- Models, Theoretical MeSH
- Feedback * MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
A new reconstruction method for parallel MRI called PROBER is proposed. The method PROBER works in an image domain similar to methods based on Sensitivity Encoding (SENSE). However, unlike SENSE, which first estimates the spatial sensitivity maps, PROBER approximates the reconstruction coefficients directly by B-splines. Also, B-spline coefficients are estimated at once in order to minimize the reconstruction error instead of estimating the reconstruction in each pixel independently (as in SENSE). This makes the method robust to noise in reference images. No presmoothing of reference images is necessary. The number of estimated parameters is reduced, which speeds up the estimation process. PROBER was tested on simulated, phantom, and in vivo data. The results are compared with commercial implementations of the algorithms SENSE and GRAPPA (Generalized Autocalibrating Partially Parallel Acquisitions) in terms of elapsed time and reconstruction quality. The experiments showed that PROBER is faster than GRAPPA and SENSE for images wider than 150x150 pixels for comparable reconstruction quality. With more basis functions, PROBER outperforms both SENSE and GRAPPA in reconstruction quality at the cost of slightly increased computational time.
- MeSH
- Algorithms MeSH
- Artifacts MeSH
- Time Factors MeSH
- Gadolinium DTPA MeSH
- Adult MeSH
- Phantoms, Imaging MeSH
- Head anatomy & histology MeSH
- Thorax anatomy & histology MeSH
- Calibration MeSH
- Contrast Media MeSH
- Humans MeSH
- Magnetic Resonance Imaging methods MeSH
- Computer Simulation MeSH
- Image Processing, Computer-Assisted methods statistics & numerical data MeSH
- Image Enhancement methods MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Comparative Study MeSH
- Names of Substances
- Gadolinium DTPA MeSH
- Contrast Media MeSH
Modelling the flow properties of rubber blends makes it possible to predict their rheological behaviour during the processing and production of rubber-based products. As the nonlinear nature of such complex processes complicates the creation of exact analytical models, it is appropriate to use artificial intelligence tools in this modelling. The present study was implemented to develop a highly efficient artificial neural network model, optimised using a novel training algorithm with fast parallel computing to predict the results of rheological tests of rubber blends performed under different conditions. A series of 120 real dynamic viscosity-time curves, acquired by a rubber process analyser for styrene-butadiene rubber blends with varying carbon black contents vulcanised at different temperatures, were analysed using a Generalised Regression Neural Network. The model was optimised by limiting the fitting error of the training dataset to a pre-specified value of less than 1%. All repeated calculations were made via parallel computing with multiple computer cores, which significantly reduces the total computation time. An excellent agreement between the predicted and measured generalisation data was found, with an error of less than 4.7%, confirming the high generalisation performance of the newly developed model.
- Keywords
- curing process, generalised regression neural network, intelligent modelling, parallel computing, rubber blends,
- Publication type
- Journal Article MeSH
Objective is a joint primary and secondary code (SC) acquisition estimator of tiered Global Navigation Satellite Systems (GNSS) signals. The estimator is based on the Parallel Code Search algorithm (PCS) combined with the Single-Block-Zero-Padding (SBZP) and the Pre-correlation Coherent Accumulation (PCA). The PCA realizes the extension of the coherent integration time in front of the PCS. However, the PCS with the SBZP and the PCA is affected by a navigation/SC bit transition problem due to its cyclic property of a computed Cross-Ambiguity Function (CAF). This CAF is degraded by diverse parasitic fragments and is not directly applicable for an acquisition. A novel analysis of this mechanism and its impact is presented. Then, the proposed modified SBZP (mSBZP) modified PCA (mPCA) PCS estimator is constructed, which does not degrade the CAF. The mSBZP allows the use of the PCS algorithm in the presence of SC bit transition, while the mPCA decreases the number of PCS algorithm calculations by a factor of SC chip count due to SC pre-correlation processing. The algorithm has the same detection performance in comparison with conventional Double-Block-Zero-Padding (DBZP). However, it allows using the PCS of half-length with longer latency up to a factor of SC chip count.
Germline DNA testing using the next-gene-ration sequencing (NGS) technology has become the analytical standard for the diagnostics of hereditary diseases, including cancer. Its increasing use places high demands on correct sample identification, independent confirmation of prioritized variants, and their functional and clinical interpretation. To streamline these processes, we introduced parallel DNA and RNA capture-based NGS using identical capture panel CZECANCA, which is routinely used for DNA analysis of hereditary cancer predisposition. Here, we present the analytical workflow for RNA sample processing and its analytical and diagnostic performance. Parallel DNA/RNA analysis allowed credible sample identification by calculating the kinship coefficient. The RNA capture-based approach enriched transcriptional targets for the majority of clinically relevant cancer predisposition genes to a degree that allowed analysis of the effect of identified DNA variants on mRNA processing. By comparing the panel and whole-exome RNA enrichment, we demonstrated that the tissue-specific gene expression pattern is independent of the capture panel. Moreover, technical replicates confirmed high reproducibility of the tested RNA analysis. We concluded that parallel DNA/RNA NGS using the identical gene panel is a robust and cost-effective diagnostic strategy. In our setting, it allows routine analysis of 48 DNA/RNA pairs using NextSeq 500/550 Mid Output Kit v2.5 (150 cycles) in a single run with sufficient coverage to analyse 226 cancer predisposition and candidate ge-nes. This approach can replace laborious Sanger confirmatory sequencing, increase testing turnaround, reduce analysis costs, and improve interpretation of the impact of variants by analysing their effect on mRNA processing.
- Keywords
- ATM, BRCA1, BRCA2, CHEK2, CZECANCA, DNA, NGS, RNA, TSC2, aberrant splicing, alternative splicing, deep intronic variant, gene expression, germline genetic testing, hereditary cancer predisposition, parallel, reproducibility, sequence capture,
- MeSH
- DNA genetics MeSH
- Genetic Predisposition to Disease * MeSH
- Humans MeSH
- Neoplasms genetics diagnosis MeSH
- Reproducibility of Results MeSH
- RNA genetics MeSH
- Sequence Analysis, DNA methods MeSH
- Sequence Analysis, RNA methods MeSH
- High-Throughput Nucleotide Sequencing * methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- DNA MeSH
- RNA MeSH
We performed intracerebral recordings of Readiness Potential (RP) and Contingent Negative Variation (CNV) with simple repetitive distal limb movement in candidates for epilepsy surgery. In 26 patients (in Paris), depth electrodes were located in various cortical structures; in eight patients (in Brno), in the basal ganglia and the cortex. RPs were displayed in the contralateral primary motor cortex, contralateral somato-sensory cortex, and bilaterally in the SMA and the caudal part of the anterior cingulate cortices. CNVs were recorded in the same cortical regions as the RP, as well as in the ipsilateral primary motor cortex, and bilaterally in the premotor fronto-lateral, parietal superior, and middle temporal regions. In the basal ganglia, the RP was recorded in the putamen in six of seven patients, and in the head of the caudate nucleus and the pallidum in the only patient with electrodes in these recording sites. We suggest that our results are consistent with a long-lasting, simultaneous activation of cortical and subcortical structures, before and during self-paced and stimulus-triggered movements. The particular regions that are simultaneously active may be determined by the task context.
- MeSH
- Electroencephalography methods MeSH
- Electrophysiology MeSH
- Electromyography MeSH
- Epilepsies, Partial physiopathology MeSH
- Contingent Negative Variation * MeSH
- Humans MeSH
- Motor Cortex physiopathology MeSH
- Brain physiopathology MeSH
- Movement physiology MeSH
- Somatosensory Cortex physiopathology MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Audio-visual integration has been shown to be present in a wide range of different conditions, some of which are processed through the dorsal, and others through the ventral visual pathway. Whereas neuroimaging studies have revealed integration-related activity in the brain, there has been no imaging study of the possible role of segregated visual streams in audio-visual integration. We set out to determine how the different visual pathways participate in this communication. We investigated how audio-visual integration can be supported through the dorsal and ventral visual pathways during the double flash illusion. Low-contrast and chromatic isoluminant stimuli were used to drive preferably the dorsal and ventral pathways, respectively. In order to identify the anatomical substrates of the audio-visual interaction in the two conditions, the psychophysical results were correlated with the white matter integrity as measured by diffusion tensor imaging.The psychophysiological data revealed a robust double flash illusion in both conditions. A correlation between the psychophysical results and local fractional anisotropy was found in the occipito-parietal white matter in the low-contrast condition, while a similar correlation was found in the infero-temporal white matter in the chromatic isoluminant condition. Our results indicate that both of the parallel visual pathways may play a role in the audio-visual interaction.
- Keywords
- DTI, Doubleflash, MRI, Multisensory, TBSS,
- MeSH
- Acoustic Stimulation MeSH
- Anisotropy MeSH
- White Matter physiology MeSH
- Adult MeSH
- Humans MeSH
- Brain Mapping MeSH
- Auditory Perception physiology MeSH
- Photic Stimulation MeSH
- Signal Detection, Psychological physiology MeSH
- Diffusion Tensor Imaging MeSH
- Imaging, Three-Dimensional MeSH
- Visual Perception physiology MeSH
- Visual Pathways physiology MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
