280 resources related to Brain mapping
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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 17th International Symposium on Biomedical Imaging (ISBI 2020)
The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 meeting will continue this tradition of fostering cross-fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.
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 Conference on Computer Vision and Pattern Recognition (CVPR)
CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.
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.
The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...
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.
Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...
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; ...
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.
Proceeding of Southwest Symposium on Image Analysis and Interpretation, 1996
Computer-aided visualization of the brain surface has numerous applications in structural and functional brain mapping for neuroscience, as well as in surgical path planning. Surface visualization of the brain using magnetic resonance (MR) images requires pixels in the images to be discriminated, or segmented into various tissue types. In this work, an automated and efficient method, based on mathematical morphology ...
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991, 1991
Proceedings. International Conference on Image Processing, 2002
For molecular brain mapping research, a reference template is necessary for integration of experimental data from different laboratories. However, the concept of the conventional brain atlas cannot provide such a reference template that fulfills our requirements. We propose a specific algorithm for model averaging to construct a 3D reference template. It extracts the geometric information of all data sets by ...
5th ISSNIP-IEEE Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living (BRC), 2014
Because of the evolution of technology and consequently, the development of advanced techniques, related to signal analysis and digitalization, has increased the use of data from brain electrical activity in clinical analysis and in researches, for example, with the use of the quantitative electroencephalography (EEGq). This is based in techniques of digital signal processing, such as, statistical analysis, transforming to ...
IEEE Transactions on Magnetics, 2010
In this paper, the abilities of the generalized cross validation (GCV) method and the L-curve method for the determination of the optimal regularization parameter are studied and compared for magnetoencephalography (MEG) source reconstruction. The results verify that the GCV method is a better choice when the measurement noise is relatively high, and the L-curve method seems to be more effective ...
Mapping Human to Robot Motion with Functional Anthropomorphism for Teleoperation and Telemanipulation with Robot Arm Hand Systems
Flying a Helicopter with Brain Waves - CES 2013
3D Body-Mapping for Severely Burned Patients - Julia Loegering - IEEE EMBS at NIH, 2019
Road-Mapping Session with Deepa Prahalad at Internet Inclusion: Advancing Solutions, Delhi, 2016
Brain Inspired Computing Systems - Luping Shi: 2016 International Conference on Rebooting Computing
Computational Intelligence for Brain Computer Interface
The EU Human Brain Project - A Systematic Path from Data to Synthesis
Q&A with Chris Berka: IEEE Brain Podcast, Episode 9
Signal Processing and Machine Learning
A Manhattan Project for the Prosthetic Arms Race
Reconstructed Brain Models for Virtual Bodies and Robots
EMBC 2011-Panel Discussion-Frontiers and Future Trends in Brain-Machine Interface
Q&A with Emery Brown: IEEE Brain Podcast, Episode 3
Q&A with Dr. Al Emondi: IEEE Brain Podcast, Episode 13
Q&A with Dr. Jennifer Gelinas: IEEE Brain Podcast, Episode 8
Q&A with Dr. Maryam Shanechi: IEEE Brain Podcast, Episode 6 Part 1
Q&A with Cindy Chestek: IEEE Brain Podcast, Episode 12
IEEE @ SXSW 2015 - DIY Brain Hacking: Electroceuticals & You
Q&A with Dr. Jacob Robinson: IEEE Brain Podcast, Episode 5
Computer-aided visualization of the brain surface has numerous applications in structural and functional brain mapping for neuroscience, as well as in surgical path planning. Surface visualization of the brain using magnetic resonance (MR) images requires pixels in the images to be discriminated, or segmented into various tissue types. In this work, an automated and efficient method, based on mathematical morphology and unsupervised clustering analysis, is proposed for segmenting 3-D MR images of the human head. The proposed method provides better rendered views of the brain surface with much less computation time, compared to a previous, direct fuzzy-based approach. The resulting rendered views of the brain surface are shown, as well as the efficiency and error analysis of the proposed methodology.
For molecular brain mapping research, a reference template is necessary for integration of experimental data from different laboratories. However, the concept of the conventional brain atlas cannot provide such a reference template that fulfills our requirements. We propose a specific algorithm for model averaging to construct a 3D reference template. It extracts the geometric information of all data sets by reconstructing the individual wireframe models, and extracts their skeletons for determining the average skeleton. Large-scale averaged models, pseudoaverage models, can be obtained by warping the individual models toward the average skeleton. The final average model can be yielded after a small-scale model averaging procedure that determines the geometric median of pseudoaverage models. In contrast with other algorithms, our algorithm allows more severe variations because of its two-level hierarchy.
Because of the evolution of technology and consequently, the development of advanced techniques, related to signal analysis and digitalization, has increased the use of data from brain electrical activity in clinical analysis and in researches, for example, with the use of the quantitative electroencephalography (EEGq). This is based in techniques of digital signal processing, such as, statistical analysis, transforming to the frequency domain, prediction and others. The topographic quantitative EEG (EEGQT) allows the creation of a scalp image showing the activity in many regions of the brain based on the quantitative analysis of the EEG signal. It gives an accurate graphical vision of the electrical activity, as well their localizations and alterations. The existing EEGQT software is based on the signal analysis on the frequency domain and gives a two-dimensional vision of the cortical activity. To obtain a more reliable EEGQT in real time, it would be important a three-dimensional mapping of the cortex. The main objective of this work is to present a proposal of architecture of a computational system capable to generate a three-dimensional brain mapping based not only on the frequency domain analysis, but in other characteristics of the EEG signals, such as, the similarity, stationarity, frequency, entropy and the signal linearity.
In this paper, the abilities of the generalized cross validation (GCV) method and the L-curve method for the determination of the optimal regularization parameter are studied and compared for magnetoencephalography (MEG) source reconstruction. The results verify that the GCV method is a better choice when the measurement noise is relatively high, and the L-curve method seems to be more effective when the source is mainly dominated by errors such as brain perturbation.
We propose a 3D interactive editor dedicated to the anatomical labelling of the cortex of the human brain. The labelling process essentially consists in the delineation and identification of the folds (or sulci) that appears at the surface of the cortex. Our tool relies on a structured set of automatically segmented objects which are the interstitial spaces contained within the folds of the cortex. We propose an interface which makes available interactions with both our structured set and the actual data being displayed along with various incidences or renderings. The tool assists the neuroanatomy expert for the identification task of the cortex and makes possible the creation of a cortex database.<<ETX>>
In the construction of topographic maps from the EEG, the Laplacian (or Source Derivation) operation improves the localisation of sources, by reducing the smearing effect in conducting layers of the head. Due to the use of a limited number of electrodes, interpolation techniques are employed either before or after applying the Laplacian. In the present work, two such approaches, Spline interpolation followed by Laplacian and Laplacian followed by four nearest neighbour interpolation, are applied to scalp potential distributions derived from simulated dipole sources. The results prove both approaches to be similarly effective in demonstrating the presence of multiple dipoles.
Investigating the shape and time to a peak, called the HR delay, of hemodynamic response (HR) gives a novel tool to analyze human brain function. We have previously proposed an analysis method for detecting activated areas and measuring HR delay simultaneously. We improve the performance of the method by modifying a mother wavelet. The modified mother wavelet is based on an HR function defined mathematically by the SPM (statistical parametric mapping) software by K.J. Friston et al. (see Human Brain Mapping, vol.2, p.189-210, 1995). To evaluate the proposed method, it and conventional methods are applied to phantom data and data from human subjects. The results indicate that the proposed method could detect activated areas equivalent to those found by conventional methods, and more accurately.
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