Conferences related to Ventricles

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2023 Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC)

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 full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.


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.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF 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.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2020 IEEE International Conference on Image Processing (ICIP)

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.


2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

All areas of ionizing radiation detection - detectors, signal processing, analysis of results, PET development, PET results, medical imaging using ionizing radiation


2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI)

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 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 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.


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Periodicals related to Ventricles

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Biomedical Engineering, IEEE Reviews in

The IEEE Reviews in Biomedical Engineering will review the state-of-the-art and trends in the emerging field of biomedical engineering. This includes scholarly works, ranging from historic and modern development in biomedical engineering to the life sciences and medicine enabled by technologies covered by the various IEEE societies.


Biomedical Engineering, IEEE Transactions on

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.


Control Systems Technology, IEEE Transactions on

Serves as a compendium for papers on the technological advances in control engineering and as an archival publication which will bridge the gap between theory and practice. Papers will highlight the latest knowledge, exploratory developments, and practical applications in all aspects of the technology needed to implement control systems from analysis and design through simulation and hardware.


Engineering in Medicine and Biology Magazine, IEEE

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.


Image Processing, IEEE Transactions on

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.


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Most published Xplore authors for Ventricles

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Xplore Articles related to Ventricles

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Activation propagation in cardiac ventricles using homogeneous monodomain model and model based on cellular automaton

2017 11th International Conference on Measurement, 2017

The activation propagation characteristics obtained when using homogeneous monodomain model (MM) of the cardiac ventricles and the model based on cellular automaton (CA) are compared in this study. The MM comprises the reaction - diffusion equation of the propagation and the modified FitzHugh- Nagumo equations of the electrical excitation of cardiac cells. This model was simulated in Comsol Multiphysics environment. ...


Automatic real-time CNN-based neonatal brain ventricles segmentation

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 ...


Simulation of late potentials using a computerized three dimensional model of the heart's ventricles with fractal conduction system

[1989] Proceedings. Computers in Cardiology, 1989

A three-dimensional model of the ventricles with a self-similar (fractal) conduction system is introduced to generate high-temporal-resolution QRS signals. The signals are obtained under normal and various damaged conditions. The obtained signals are 60-200 Hz bandpass filtered, and two parameters which have been used as markers for the presence of late potential activity are measured: (1) the filtered QRS duration ...


Simultaneous segmentation of the left and right heart ventricles in 3D cine MR images of small animals

Computers in Cardiology, 2005, 2005

New high resolution image techniques allow to capture the anatomy and movement of the heart of small animals. The availability of these in vivo images can be very useful for medical research, however the amount of generated data for large animal studies makes manual analysis a very tedious task. To cope with the problem of automatic analysis of these images, ...


A fast and accurate tracking algorithm of left ventricles in 3D echocardiography

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008

Tracking of left ventricles in 3D echocardiography is a challenging topic because of the poor quality of ultrasound images and the speed consideration. In this paper, a fast and accurate learning based 3D tracking algorithm is presented. A novel one-step forward prediction is proposed to generate the motion prior using motion manifold learning. Collaborative trackers are introduced to achieve both ...


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Educational Resources on Ventricles

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IEEE.tv Videos

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IEEE-USA E-Books

  • Activation propagation in cardiac ventricles using homogeneous monodomain model and model based on cellular automaton

    The activation propagation characteristics obtained when using homogeneous monodomain model (MM) of the cardiac ventricles and the model based on cellular automaton (CA) are compared in this study. The MM comprises the reaction - diffusion equation of the propagation and the modified FitzHugh- Nagumo equations of the electrical excitation of cardiac cells. This model was simulated in Comsol Multiphysics environment. Model based on CA was simulated in Matlab program environment. Realistic activation time of about 80 ms was obtained for the whole ventricles when activation was started in nine analytically defined points. Differences in activation times obtained from the numerical solutions using MM and CA models were less than ±10 ms.

  • Automatic real-time CNN-based neonatal brain ventricles segmentation

    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.

  • Simulation of late potentials using a computerized three dimensional model of the heart's ventricles with fractal conduction system

    A three-dimensional model of the ventricles with a self-similar (fractal) conduction system is introduced to generate high-temporal-resolution QRS signals. The signals are obtained under normal and various damaged conditions. The obtained signals are 60-200 Hz bandpass filtered, and two parameters which have been used as markers for the presence of late potential activity are measured: (1) the filtered QRS duration and (2) the root-mean-square voltage of the last 40 ms. The effects of the ventricular conditions on the two parameters are described. It is demonstrated that the late potential activity can be attributed to a regional reduction in propagation velocity but that this is not a sufficient condition for their detection.<<ETX>>

  • Simultaneous segmentation of the left and right heart ventricles in 3D cine MR images of small animals

    New high resolution image techniques allow to capture the anatomy and movement of the heart of small animals. The availability of these in vivo images can be very useful for medical research, however the amount of generated data for large animal studies makes manual analysis a very tedious task. To cope with the problem of automatic analysis of these images, we propose the use of the deformable elastic template method to perform automatic segmentation of the ventricles. To adapt the method to the specificities of high-resolution MRI, several improvements are presented, including an image-context dependent scheme for more robust segmentation. Qualitative results show that our method is able to correctly retrieve the heart's contours in 3D

  • A fast and accurate tracking algorithm of left ventricles in 3D echocardiography

    Tracking of left ventricles in 3D echocardiography is a challenging topic because of the poor quality of ultrasound images and the speed consideration. In this paper, a fast and accurate learning based 3D tracking algorithm is presented. A novel one-step forward prediction is proposed to generate the motion prior using motion manifold learning. Collaborative trackers are introduced to achieve both temporal consistence anproc biomedical optical ima image segmentation cellular biophys fluores biology comd tracking robustness. The algorithm is completely automatic and computationally efficient. The mean point-to-mesh error of our algorithm is 1.28 mm. It requires less than 1.5 seconds to process a 3D volume (160 x 148 x 208 voxels).

  • Precise segmentation of the lateral ventricles and caudate nucleus in MR brain images using anatomically driven histograms

    This paper demonstrates a time-saving, automated method that helps to segment the lateral ventricles and caudate nucleus in T1-weighted coronal magnetic resonance (MR) brain images of normal control subjects. The method involves choosing intensity thresholds by using anatomical information and by locating peaks in histograms. To validate the method, the lateral ventricles and caudate nucleus were segmented in three brain scans by four experts, first using an established method involving isointensity contours and manual editing, and second using automatically generated intensity thresholds as an aid to the established method. The results demonstrate both time savings and increased reliability.

  • Assessment of blood flow velocity profiles in heart ventricles and aorta with phase contrast magnetic resonance imaging

    Accurate measurement of blood flow is usually very difficult and invasive to make in spite of its important roles in clinical diagnosis. Therefore, an alternative method capable of determining the cardiac output non-invasively will be of good use. Furthermore, measurement of blood velocity with high resolution either in the heart or in any part of circulatory system without any cardiac catheterization would play an important role in the evaluation of patients with circulatory disorders. The MRI phase contrast technique (PC-MRI) can be used for this purpose. It can provide flow velocity information in addition to anatomic imaging by applying bipolar gradient in the velocity encoding direction. We can obtain velocity encoded MR images computed by the phase difference between two images acquired with different gradient first moments but identical zeroth moments. We combined phase contrast sequence and cine method to acquire the velocity map across the entire cardiac cycle. ECG gating was used for triggering. We calculated volume flow by pixel unit velocity analysis in the region of interest. Also by visualizing the velocity profile dynamically with 3D representation, we could assess more easily how the appearances of blood flow patterns are. The proposed method was tested both with a phantom where a pulsatile waveform was generated by ventricular assistance device and in vivo at the heart of normal volunteer on a GE 1.5 T scanner. As a conclusion, the dynamically represented 3D images obtained by the cine PC method could be confirmed as a good method for assessment of cardiac function.

  • In Silico Investigation of Electrically Silent Acute Cardiac Ischemia in the Human Ventricles

    Acute cardiac ischemia, which is caused by the occlusion of a coronary artery, often leads to lethal ventricular arrhythmias or heart failure. The early diagnosis of this pathology is based on changes of the electrocardiogram (ECG), i.e., mainly shifts of the ST segment. However, the underlying mechanisms responsible for these shifts are not completely understood. Furthermore, clinical observations indicate that some acute ischemia cases can hardly be detected using standard 12-lead ECG only. Therefore, multiscale computer simulations of cardiac ischemia using realistic models of human ventricles were carried out in this work. For this purpose, the transmembrane voltage distributions in the heart and the corresponding body surface potentials were computed with varying transmural extent of the ischemic region at different ischemia stages. Some of the simulated ischemia cases were “ electrically silent,” i.e., they could hardly be identified in the 12-lead ECG.

  • Auto detection of brain ventricles using Hausdorff distance

    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.

  • Modeling the effects of amiodarone on short QT syndrome variant 2 in the human ventricles

    Aims: The short QT syndrome (SQTS) is a new genetic disorder associated with atrial and ventricular arrhythmias and sudden death. The SQT2, SQTS variant, results from a gain-of-function mutation (V307L) in the KCNQ1-encoded potassium channel. Although pro-arrhythmogenic effects of SQTS have been characterized, less is known about the pharmacology of SQTS. Therefore, this study aims to assess the effects of amiodarone on SQT2. Methods and Results: The ten Tusscher et al. model of the human ventricular action potential (AP) was modified to incorporate changes to IKsbased on experimental data. Cell models were incorporated into heterogeneous one-dimensional (1D) tissue to compute the pseudo-ECG and the corresponding QT interval. The blocking effects of amiodarone on IKs, INa, INaK, ICaL, INaCa, and IKrwere modeled using nH(Hill coefficient) and IC50values from the literature. At the cellular level, amiodarone both at low and high doses prolonged the SQT2 AP duration (APD); at the tissue level, amiodarone at a high dose caused QT prolongation to the physiological range, but failed at a low dose. Conclusions: Amiodarone at a high dose produced better therapeutic effects on SQT2 than at a low dose. This study provides new evidence that amiodarone at a high dose may be a potential pharmacological treatment for SQT2.



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