404 resources related to Multiple sclerosis
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2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
FUZZ-IEEE 2021 will represent a unique meeting point for scientists and engineers, both from academia and industry, to interact and discuss the latest enhancements and innovations in the field. The topics of the conference will cover all the aspects of theory and applications of fuzzy sets, fuzzy logic and associated approaches (e.g. aggregation operators such as the Fuzzy Integral), as well as their hybridizations with other artificial and computational intelligence techniques.
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.
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.
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.
The IEEE Computational Intelligence Magazine (CIM) publishes peer-reviewed articles that present emerging novel discoveries, important insights, or tutorial surveys in all areas of computational intelligence design and applications.
Both general and technical articles on current technologies and methods used in biomedical and clinical engineering; societal implications of medical technologies; current news items; book reviews; patent descriptions; and correspondence. Special interest departments, students, law, clinical engineering, ethics, new products, society news, historical features and government.
Signal-processing aspects of image processing, imaging systems, and image scanning, display, and printing. Includes theory, algorithms, and architectures for image coding, filtering, enhancement, restoration, segmentation, and motion estimation; image formation in tomography, radar, sonar, geophysics, astronomy, microscopy, and crystallography; image scanning, digital half-toning and display, andcolor reproduction.
Telemedicine, teleradiology, telepathology, telemonitoring, telediagnostics, 3D animations in health care, health information networks, clinical information systems, virtual reality applications in medicine, broadband technologies, and global information infrastructure design for health care.
 Proceedings of the Twelfth Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1990
IEEE Engineering in Medicine and Biology Magazine, 2008
Therapeutic robots enhance clinician productivity in facilitating patient recovery. In this article, we presented an overview of the remarkable growth in the activities in the area of therapeutic robotics and of experiences with our devices. We briefly review the published clinical literature in this emerging field and our initial clinical results in stroke. However, we also report our initial efforts ...
3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006., 2006
Automatic brain segmentation is an issue of specific clinical relevance in both diagnosis and therapy control of patients with demyelinating diseases such as multiple sclerosis (MS). We present a complete system for high- precision computer-assisted image analysis of multispectral MRI data based on a flexible machine learning approach. Careful quality evaluation shows that the system outperforms conventional threshold-based techniques w.r.t. ...
Proceedings 13th IEEE Symposium on Computer-Based Medical Systems. CBMS 2000, 2000
Proton magnetic resonance spectroscopic imaging (MRSI) of the brain was performed on 53 patients with clinically definite relapsing remitting multiple sclerosis (MS). The contributions of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) to the spectroscopic voxels were determined using either double inversion recovery magnetic resonance imaging or segmentation of affirmative images. In 13 patients additional peaks in ...
3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006., 2006
This paper presents a novel hybrid segmentation technique incorporating a statistical as well as a geometric model in a unified segmentation scheme for brain tissue segmentation of magnetic resonance imaging (MRI) scans. We combine both voxel probability and image gradient and curvature information for segmenting gray matter (GM) and white matter (WM) tissues. Both qualitative and quantitative results on synthetic ...
Arogyaswami J. Paulraj
Brooklyn 5G - 2015 - Edward G. Tiedemann Jr. - Multiple Antennas in Wireless Systems (MAWS)
26th Annual MTT-AP Symposium and Mini Show - Ken Kenjale
Cloud Computing Potential Role in Transforming India
Multiple Sensor Fault Detection and Isolation in Complex Distributed Dynamical Systems
SIMD Programming in VOLK, the Vector-Optimized Library of Kernels
IMS 2014: Super High Bit Rate Radio Access Technologies for Small Cells Using Higher Frequency Bands
The Other 5G: 60 GHz Wifi Access / B-Haul Solutions - Arogyaswami Paulraj - Brooklyn 5G Summit 2018
Ashutosh Dutta interviewed at India Mobile Congress 2018
IEEE WEBINAR SERIES-April 2, 2014 - Understanding Mosfet Parameters: We Do Need Even More Footnotes in Mosfet Datasheets
Carrier Aggregation Receivers - Shimi Shilo & Dror Regev - RFIC Showcase 2018
Comparing Modern Multiport VNA vs. Conventional Switch-based VNA: MicroApps 2015 - Keysight Technologies
RF as the Differentiator (RFIC 2015 Keynote)
Fast Broadband Impedance Matching with Automatic Circuit Synthesis: MicroApps 2015 - Keysight Technologies
Indian Institute of Technology Madras accepts the Spectrum Technology in the Service of Society Award - Honors Ceremony 2017
Choosing the Right Connectivity Technology for your IoT Application - Geoff Mulligan - 5G World Forum Santa Clara 2018
Scalable and Reconfigurable Tap-Delay-Line for Multichannel Equalization - Ari Willner - Closing Ceremony, IPC 2018
Karin Hollerbach: Far Futures Panel - TTM 2018
IEEE Magnetics 2014 Distinguished Lectures - JONATHAN COKER
Therapeutic robots enhance clinician productivity in facilitating patient recovery. In this article, we presented an overview of the remarkable growth in the activities in the area of therapeutic robotics and of experiences with our devices. We briefly review the published clinical literature in this emerging field and our initial clinical results in stroke. However, we also report our initial efforts that go beyond stroke, broadening the potential population that might benefit from this class of technology by discussing case studies of applications to other neurological diseases. We will also highlight the underexploited potential of this technology as an evaluation tool.
Automatic brain segmentation is an issue of specific clinical relevance in both diagnosis and therapy control of patients with demyelinating diseases such as multiple sclerosis (MS). We present a complete system for high- precision computer-assisted image analysis of multispectral MRI data based on a flexible machine learning approach. Careful quality evaluation shows that the system outperforms conventional threshold-based techniques w.r.t. inter- observer agreement levels for the quantification of relevant clinical parameters, such as white matter lesion load and brain parenchyma volume
Proton magnetic resonance spectroscopic imaging (MRSI) of the brain was performed on 53 patients with clinically definite relapsing remitting multiple sclerosis (MS). The contributions of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) to the spectroscopic voxels were determined using either double inversion recovery magnetic resonance imaging or segmentation of affirmative images. In 13 patients additional peaks in the 0.8 to 1.5 ppm spectral region, that reflect the demyelinating products, were observed mainly confined to GM. These studies demonstrate that some of the GM that appears normal on magnetic resonance images is biochemically abnormal.
This paper presents a novel hybrid segmentation technique incorporating a statistical as well as a geometric model in a unified segmentation scheme for brain tissue segmentation of magnetic resonance imaging (MRI) scans. We combine both voxel probability and image gradient and curvature information for segmenting gray matter (GM) and white matter (WM) tissues. Both qualitative and quantitative results on synthetic and real brain MRI scans indicate superior and consistent performance when compared with standard techniques such as SPM and FAST
Flow and structural related studies of the vasculature of the head and neck have indicated that venous outflow may be obstructed in MS patients, with postulation that this leads to the development or exacerbation of the disease. The current work presented in the following is to determine if there is correlation between abnormal internal jugular vein (IJV) flow and average cerebral blood flow in MS patients. 140 MS patients, 117 of known MS type, and 26 healthy controls were imaged by 3-T MRI. 3D contrast-enhanced MR angiography was assessed for structural abnormalities of the IJV, and the MS group was subdivided into two groups; those with stenosis and those without. Velocity encoded phase contrast MR data was processed to quantify flow through major arteries and veins of the neck. The average cerebral blood flow (CBF) was calculated by normalizing the total arterial blood flow to the brain, taken by adding the flow of the internal carotid arteries and vertebral arteries at the C2 vertebral level, by the total brain volume quantified from 3D FLAIR data. The average CBF as a function of total IJV flow at the C6 vertebral level was presented. The MS patients without stenosis show a linear trend in average CBF vs total IJV flow, indicating a potential relationship between arterial flow to the brain and effective drainage in the supine position through the IJV. Future research may indicate potential flow related biomarkers which further separate healthy controls and MS patients.
A new recording system was established for the detection of 1a reciprocal inhibition of soleus H-reflex by using the percutaneously implanted electrodes for conditioning and test stimulation those applied to deep peroneal nerve and tibial nerve respectively. This system has its advantage in stable and reliable H-reflex recording even under such conditions as during stimulating other nerves, loading mechanical force and motion in lower extremity. By using this system, the increase of the 1a reciprocal inhibition was detected immediately after TES for common peroneal nerve in hemiplegic patients.
While a body of literature relating cognition and oculomotor performance exists, a better understanding of these processes would help facilitate the development of effective treatments for patients suffering various neurological disorders, such as Multiple Sclerosis (MS), Huntington's Disease, or a traumatic brain injury. To examine the relationship between the two, we sought to measure cognition and oculomotor functioning simultaneously, through a modification of a commonly used neuropsychological test, the Symbol Digit Modalities Test (SDMT). Measurement includes monitoring of eye movements in two dimensions with the aid of infrared tracking. This paper presents preliminary data and an overview of analytical methods to be performed in the future on patients with neurological disorders. Correlations between eye movements and the mSDMT were verified using signal characterization. Furthermore, saccadic velocity was shown to remain relatively constant in healthy controls.
There is a growing demand for powered wheelchairs to provide mobility for people with upper-limb impairments, i.e., individuals suffering from cerebral palsy, paraplegia, or multiple sclerosis, and others who may depend on a human-friendly wheelchair to conduct their daily activities. The design of the multiple master multiple slave ("M3S") architecture provides a flexible system in which individual devices can be added or removed to accommodate specific needs. The M3S provides a two-level safety system for each device. The two levels are a central safety monitor and the two independent wired-OR safety lines connected to each device on the bus, and the system is configured such that in the event of failure, system shutdown can be independently enabled at each separate safety level. We have implemented a prototype with DSP cores and additional circuitries that provide safety enhancements to the M3S protocol, and configured the input subsystems and output prime mover to fit into this novel system.
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