Search results for "Computer Science"
showing 10 items of 22367 documents
Projection and Pinhole-Based Data Acquisition for Small-Animal SPECT Using Storage Phosphor Technology
2007
Three-dimensional Single Photon Emission Computed Tomography (SPECT) can provide high-resolution insight into biomolecular distribution and pharmacokinetics. However, instrument availability and distribution is limited at present,and imaging times can be considerable. To evaluate the large array of novel agents which are becoming available,we find that storage phosphor-based in vivo imaging can provide an important,rapid-throughput transition from the traditional ex vivo sacrifice/gamma counting and autoradiography to full-time course SPECT.
The number of contacts in random fibre networks
2012
There is a wide range of materials that can be considered as nonwoven random networks of fibres. Such materials include glass-fibre mats, filters, various paper products and structural components of cells and tissues. The mechanical properties of these kinds of networks have been studied extensively for many decades. As many of such networks form more or less two-dimensional structures, they can, to a good approximation, be considered to consist of randomly distributed fibres or filaments connected at their crossings points. Recent development of the resolution of X-ray computed tomography have enabled imaging of the three dimensional structure of such materials with a resolution sufficient…
Kinetic analysis of functional images: The case for a practical approach to performance prediction
1999
We present the first parallel medical application for the analysis of dynamic positron emission tomography (PET) images together with a practical performance model. The parallel application may improve the diagnosis for a patient (e. g. in epilepsy surgery) because it enables the fast computation of parametric images on a pixed level as opposed to the traditionally used region of interest (ROI) approach which is applied to determine an average parametric value for a particular anatomic region of the brain. We derive the performance model from the application context and show its relation to abstract machine models. We demonstrate the accuracy of the model to predict the runtime of the appli…
Measuring Functional Connectivity of Human Intra-Cortex Regions with Total Correlation
2021
The economy of brain organization makes the primate brain consume less energy but efficiency. The neurons densely wired each other dependent on both anatomy structure connectivity and functional connectivity. Here, I only describe functional connectivity with Functional Magnetic Resonance Imaging (fMRI) data. Most importantly, how to quantitative measure information share or separate among functional brain regions, what’s worse, fMRI data exist large dimensional problems or “curse dimensionality” [1]. However, the multivariate total correlation method can perfectly address the above problems. In this paper, two things measured with the information-theoretic technique - total correlation [2,…
Clustering Algorithms for MRI
1991
Magnetic Resonance Imaging (MRI) plays a relevant role in the design of systems for computer assisted diagnosis. MR-images are multi-dimensional in nature; physicians have to combine several perceptual information images to perform the tissue classification needed for diagnosis. Automatic clustering methods help to discriminate relevant features and to perform a preliminary segmentation of the image; it can guide the final manual classification of body-tissues. Three clustering techniques and their integration in a MRI-system are described. Their performance and accuracy was evaluated on synthetic and real image-data. A comparison of our approach with the tissue-classification done by a rad…
Classification of Schizophrenia Patients and Healthy Controls Using ICA of Complex-Valued fMRI Data and Convolutional Neural Networks
2019
Deep learning has contributed greatly to functional magnetic resonance imaging (fMRI) analysis, however, spatial maps derived from fMRI data by independent component analysis (ICA), as promising biomarkers, have rarely been directly used to perform individualized diagnosis. As such, this study proposes a novel framework combining ICA and convolutional neural network (CNN) for classifying schizophrenia patients (SZs) and healthy controls (HCs). ICA is first used to obtain components of interest which have been previously implicated in schizophrenia. Functionally informative slices of these components are then selected and labelled. CNN is finally employed to learn hierarchical diagnostic fea…
Digital Acquisition and Processing of Video Angiocardiograms
1986
Angiocardiographic diagnosis is still mainly based on the visual assessment of radiographic projection images recorded on photographic film. Considerable amounts of contrast material have to be selectively injected into the circulation in order to make the regions of diagnostic relevance visible in the superposition of the shadows of tissue and bone structures displayed in these transmission images. In addition, selective angiocardiography requires exact positioning of the catheter, a time-consuming procedure which is not without risk. The processing of the angiographie films obtained is difficult to maintain at a constant high quality level, and this introduces an disadvantageous delay bet…
Increasing Stability of EEG Components Extraction Using Sparsity Regularized Tensor Decomposition
2018
Tensor decomposition has been widely employed for EEG signal processing in recent years. Constrained and regularized tensor decomposition often attains more meaningful and interpretable results. In this study, we applied sparse nonnegative CANDECOMP/PARAFAC tensor decomposition to ongoing EEG data under naturalistic music stimulus. Interesting temporal, spectral and spatial components highly related with music features were extracted. We explored the ongoing EEG decomposition results and properties in a wide range of sparsity levels, and proposed a paradigm to select reasonable sparsity regularization parameters. The stability of interesting components extraction from fourteen subjects’ dat…
Functional Near Infrared Spectroscopy System Validation for Simultaneous EEG-FNIRS Measurements
2019
Functional near-infrared spectroscopy (fNIRS) applied to brain monitoring has been gaining increasing relevance in the last years due to its not invasive nature and the capability to work in combination with other well–known techniques such as the EEG. The possible use cases span from neural-rehabilitation to early diagnosis of some neural diseases. In this work a wireline FPGA–based fNIRS system, that use SiPM sensors and dual-wavelength LED sources, has been designed and validated to work with a commercial EEG machine without reciprocal interference.
Miniature wireless photoplethysmography devices: integration in garments and test measurements
2012
Wireless PPG devices were developed and embedded in everyday clothes (bandage, scarf, cycling glove and wrist strap) to monitor cardiovascular state of free-moving persons. The corresponding software for measurements also has been developed and tested in laboratory. Real-time measurements of PPG signals were taken in parallel with a professional ECG reference device, and high correlation was demonstrated.