64 resources related to Brain Ventricles
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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 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.
All areas of ionizing radiation detection - detectors, signal processing, analysis of results, PET development, PET results, medical imaging using ionizing radiation
The world's premiere conference in MEMS sensors, actuators and integrated micro and nano systems welcomes you to attend this four-day event showcasing major technological, scientific and commercial breakthroughs in mechanical, optical, chemical and biological devices and systems using micro and nanotechnology.The major areas of activity in the development of Transducers solicited and expected at this conference include but are not limited to: Bio, Medical, Chemical, and Micro Total Analysis Systems Fabrication and Packaging Mechanical and Physical Sensors Materials and Characterization Design, Simulation and Theory Actuators Optical MEMS RF MEMS Nanotechnology Energy and Power
No periodicals are currently tagged "Brain Ventricles"
2010 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), 2010
Brain plays an important role in human anatomy. The brain ventricular system can often be affected by different kinds of brain lesion, to the extent of creating an imbalance problem in the brain system. Hence, it is useful to develop a method to check the brain condition and to detect the existence of ventricles as well. A template of the ...
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 2018
Quantitative imaging of brain plays an important role in preterm neonates with a very low birth weight due to the increased risk of developing intraventricular hemorrhage (IVH). In this work, we propose a fully automated method for segmentation of ventricles from two-dimensional (2D) ultrasound (US) scans. The proposed method is based on a Convolutional Neural Network (CNN) that combines the ...
3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006., 2006
We use point distribution models (PDMs) to investigate lateral asymmetries in the shape of brain ventricles between control subjects and people with schizophrenia. Ventricle surfaces were extracted from T2-weighted MR images and PDMs generated using structural correspondences on the individual surfaces. Using paired linear discriminant analysis we calculate the vector in shape space that maximally separates the shapes of right ...
Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA 2001), 2001
Enlarged ventricular size and/or asymmetry have been found markers for psychiatric illness, including schizophrenia. However, this morphometric feature is non-specific and occurs in many other brain diseases, and its variability in healthy controls is not sufficiently understood. We studied ventricular size and shape in 3D MRI (N=20) of monozygotic (N=5) and dizygotic (N=5) twin pairs. Left and right lateral, third ...
2008 15th IEEE International Conference on Image Processing, 2008
One of the hallmarks of Alzheimer's disease (AD) is the loss of neurons in the brain. In many cases, the medical experts use MR (magnetic resonance) images to qualitatively measure the neuronal loss by the shrinkage (atrophy) of the structures-of-interest, or sometimes more easily by the enlargement of the fluid-filled structures, such as the ventricles. For quantitative analysis, volume is ...
Reconstructed Brain Models for Virtual Bodies and Robots
Brain Inspired Computing Systems - Luping Shi: 2016 International Conference on Rebooting Computing
The EU Human Brain Project - A Systematic Path from Data to Synthesis
Signal Processing and Machine Learning
Computational Intelligence for Brain Computer Interface
Q&A with Dr. Jacob Robinson: IEEE Brain Podcast, Episode 5
Q&A with Chris Berka: IEEE Brain Podcast, Episode 9
EMBC '09 - Technology's Role in Understanding and Treating Conditions of the Brain.
A Manhattan Project for the Prosthetic Arms Race
EMBC 2011-Panel Discussion-Frontiers and Future Trends in Brain-Machine Interface
Scientific Discovery & Deep Brain Stimulation: Jerrold Vitek, MD, PhD
EMBC 2011-Keynote-Kamil Ugurbil-Frontiers in Neuroimaging: from Cortical Columns to Whole Brain Function, Connectivity and Morphology
Q&A with Dr. Al Emondi: IEEE Brain Podcast, Episode 13
IEEE @ SXSW 2015 - DIY Brain Hacking: Electroceuticals & You
Q&A with Dr. Maryam Shanechi: IEEE Brain Podcast, Episode 6 Part 1
Q&A with Kip Ludwig: IEEE Brain Podcast, Episode 7
Q&A with Emery Brown: IEEE Brain Podcast, Episode 3
Q&A with Jack Gallant: IEEE Brain Podcast, Episode 11
Q&A with Eric Perreault: IEEE Brain Podcast, Episode 1
Brain plays an important role in human anatomy. The brain ventricular system can often be affected by different kinds of brain lesion, to the extent of creating an imbalance problem in the brain system. Hence, it is useful to develop a method to check the brain condition and to detect the existence of ventricles as well. A template of the ventricle is first created. Then ventricle detection in a slice of brain scan is done by using the Hausdorff distance. The presence of ventricles is smoothed by a median filter. Then, the ventricles are split into left and right halves through the computed centroid. Ratio is calculated to detect the brain abnormality. Result showed that 50% of the patients were detected accurately based on the ventricles.
Quantitative imaging of brain plays an important role in preterm neonates with a very low birth weight due to the increased risk of developing intraventricular hemorrhage (IVH). In this work, we propose a fully automated method for segmentation of ventricles from two-dimensional (2D) ultrasound (US) scans. The proposed method is based on a Convolutional Neural Network (CNN) that combines the advantages of U-Net and SegNet architectures for ventricles segmentation. Extensive experiments on a dataset consisting of 687 US scans show that the proposed method achieves significant improvements over the state-of-the-art medical image segmentation methods.
We use point distribution models (PDMs) to investigate lateral asymmetries in the shape of brain ventricles between control subjects and people with schizophrenia. Ventricle surfaces were extracted from T2-weighted MR images and PDMs generated using structural correspondences on the individual surfaces. Using paired linear discriminant analysis we calculate the vector in shape space that maximally separates the shapes of right and left ventricles in the group. The magnitude of the asymmetry is quantified by projection of the individual ventricle shapes onto this vector. We observe significant differences in the magnitude of the asymmetry in both schizophrenia and control groups. There is also a clear difference in the pattern of asymmetry. Male and female subgroups show different magnitudes and patterns of asymmetry, in both groups
Enlarged ventricular size and/or asymmetry have been found markers for psychiatric illness, including schizophrenia. However, this morphometric feature is non-specific and occurs in many other brain diseases, and its variability in healthy controls is not sufficiently understood. We studied ventricular size and shape in 3D MRI (N=20) of monozygotic (N=5) and dizygotic (N=5) twin pairs. Left and right lateral, third and fourth ventricles were segmented from high-resolution T1w SPGR MRI using supervised classification and 3D connectivity. Surfaces of binary segmentations of left and right lateral ventricles were parametrized and described by a series expansion using spherical harmonics. Objects were aligned using the intrinsic coordinate system of the ellipsoid described by the first order expansion. The metric for pairwise shape similarity was the mean squared distance (MSD) between object surfaces. Without normalization for size, MZ twin pairs only showed a trend to have more similar lateral ventricles than DZ twins. After scaling by individual volumes, however, the pairwise shape difference between right lateral ventricles of MZ twins became very small with small group variance, differing significantly from DZ twin pairs. This finding suggests that there is new information in shape not represented by size, a property that might improve understanding of neurodevelopmental and neurodegenerative changes of brain objects and of heritability of size and shape of brain structures. The findings further suggest that alignment and normalization of objects are key issues in statistical shape analysis which need further exploration.
One of the hallmarks of Alzheimer's disease (AD) is the loss of neurons in the brain. In many cases, the medical experts use MR (magnetic resonance) images to qualitatively measure the neuronal loss by the shrinkage (atrophy) of the structures-of-interest, or sometimes more easily by the enlargement of the fluid-filled structures, such as the ventricles. For quantitative analysis, volume is the common choice. Volume, or area in 2D, is a gross measure and it cannot capture shape differences that can improve the diagnostic accuracy. Because most existing methods use complex and difficult- to-reproduce shape descriptors, the experts prefer more easily and robustly extractable area and volume in their diagnosis. In this paper, we introduce several novel and easily-extractable 2D shape descriptors for brain ventricle, and show that they and some of the well-known simple shape descriptors, such as perimeter, are better descriptors in the classification of AD patients and healthy controls.
Computer assisted medical image processing can extract vital information that may be elusive to human eyes. In this paper, an algorithm is proposed to automatically estimate the position of the actual midline from the brain CT scans using multiple regions shape matching. The method matches feature points identified from a set of ventricle templates, extracted from MRI, with the corresponding feature points in the segmented ventricles from CT images. Then based on the matched feature points, the position of the actual midline is estimated. The proposed multiple regions shape matching algorithm addresses the deformation problem arising from the intrinsic multiple regions nature of the brain ventricles. Experiments on the CT scans from patients with traumatic brain injuries (TBI) show promising results, particularly the proposed algorithm proves to be quite robust.
Current high frequency ultrasound imaging, or ultrasound biomicroscopy (UBM) systems have the capability of imaging mouse embryos with a frame rate of up to 200 frames per second. 3D datasets can also be acquired with the appropriate hardware. Because of the limited depth of field (DOF), effective volumetric analysis is limited to approximately 2 mm about the passive focus for a fixed-focus transducer operating at 40 MHz. This shortcoming imposes a size limit which the current technology can effectively be used to segment out accurate volumetric anatomy of the embryonic mouse, Previously we reported the fabrication a five-element 40-MHz annular array and an array imaging system. Wire phantom measurements with this array reveals an increase in DOF from 1-2 mm (fixed-focus) to more than 10 mm with array focusing. When imaging attenuating media such as mouse embryos, it is expected that the figures of merit for the array images, such as the signal to noise ratio (SNR) and the depth of field (DOF) will be reduce. Images from mouse embryos from at gestational ages 11 (E11.5) and 13 (E13.5) were acquired with this annular array system, and show the superior image definition and quality over the fixed-focus images. Quantitative estimates of the SNR and DOF were calculated, and segmentation of the brain ventricles was accomplished for both gestational ages
Preliminary results of applying the advanced three-dimensional visualization techniques of volumetric rendering to represent state-of-the art magnetic resonance images of the ventricular system are reported. Cinematic loops provide the subjective impression of a rotating 3-D object in space, thus enhancing the appreciation of the 3-D structure. Different images were obtained by changing the color/opacity parameters and transparency factors. Only minimal editing was required to obtain the judges. It was not necessary to trace the precise ventricular borders as is usually required in computer graphics approaches. Initial results suggest that volumetric display of magnetic resonance images of the brain can be of value for the assessment of the ventricular system deep with the brain paraenchyma.<>
Computational fluid dynamic (CFD) simulations have provided detailed information about the complex flow and pressure field within the cerebrospinal fluid (CSF) system. The solutions of these simulations are sensitive to boundary conditions and thus need validation with in vivo measurements. However, validation of CFD flow results and MRI CSF flow measurements have been limited to through-plane pcMR measurements. Recent advancements in MRI flow measurement technology has enabled measurement of the 4D flow field within the spinal subarachnoid space (SSS), superior sagittal sinus and ventricles of the brain. Alterations in cerebrospinal fluid (CSF) dynamics have been associated with neurological symptoms and formation of Syringomyelia in patients with Chiari malformation and spinal stenosis. In these patients, analysis of morphology alone has proved to be insufficient in explaining the absence or presence of symptoms. In the present study, we compare quantitatively 4D flow measurements to CFD analysis within the SSS (C1-T1, cervical spinal segment) of a healthy volunteer without any lesions at the craniocervical junction or the cervical spinal canal.
Hydrocephalus is a medical condition characterized by an excessive accumulation of cerebrospinal fluid (CSF) in the ventricles of the brain, typically causing an increase in patient intracranial pressure (ICP). The increased ICP can result in headache, nausea, vomiting, and even death. To combat this potentially dangerous elevated ICP, physicians often use surgically implemented brain shunt systems that drain excess CSF from the brain into the abdominal cavity. Monitoring of ICP in patients with hydrocephalus is crucial for the effective management of brain shunt systems. Currently, clinical ICP measurement approaches are typically invasive and are performed using intraventricular catheters placed through a drilled hole in the skull. Home monitoring of ICP may be advantageous for tracking patient clinical status. A noninvasive method would be particularly useful for ICP monitoring in the emergency department, doctor's office, home and other non- ICU settings. This study aims to explore the correlation between ICP and tympanometric parameters including static acoustic compliance, a measurement of middle ear pressure at maximum compliance. Tympanometry was performed on subjects who rested on a tilt table at varying tilt angles, which induces changes in ICP. Results suggested a correlation between tilt angles and pressure of the middle ear at peak compliance. Tympanometry may provide a noninvasive method for monitoring ICP.
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