Search results for "Computer"
showing 10 items of 30657 documents
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.
A Knowledge-Based System for the Diagnosis of Alzheimer’s Disease
2003
Therapies to slow down the progression of Alzheimer’s disease are most effective when applied in its initial stages. Therefore it is important to develop methods to diagnose the disease as early as possible. It is also desirable to establish standards which can be used generally by physicians who may not be experts in diagnosis of the disease. One possible method to obtain an early diagnosis is the evaluation of the glucose metabolism of the brain. In this paper we present a prototype of an expert system that automatically diagnoses Alzheimer’s disease on the basis of positron emission tomography images displaying the metabolic activity in the brain.
Real and simulated endoscopy of neurosurgical approaches in an anatomical model
1997
Endoscopy simulation is a new visualisation technique which can be used to visualise patient anatomy as seen through endoscopes. In the following, we describe the application of simulated endoscopy to neurosurgical endoscopic approaches. We assess different aspects of virtual images and their influence on the final result, as judged by clinicians. One of these aspects is the projective geometry which is used to render the 3D images. Rendering using stereographic projection leads to more realistic endoscopic views than perspective projection.
Study of CT/MRI mutual information based registration applied in brachytherapy
2016
The present work aims to include magnetic resonance imaging (MRI) in a Medical Image-based Graphical platfOrm - Brachytherapy module (AMIGOBrachy) which coupled to the Monte Carlo N-Particle (MCNP6) code allows absorbed dose calculations. Computed tomography (CT) and MRI images were registered using mutual information algorithms to improve tissue segmentation potentially leading to a more accurate treatment planning system.
Macrolides May Prevent Severe Acute Respiratory Syndrome Coronavirus 2 Entry into Cells: A Quantitative Structure Activity Relationship Study and Exp…
2021
The global pandemic caused by the emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is threatening the health and economic systems worldwide. Despite the enormous efforts of scientists and clinicians around the world, there is still no drug or vaccine available worldwide for the treatment and prevention of the infection. A rapid strategy for the identification of new treatments is based on repurposing existing clinically approved drugs that show antiviral activity against SARS-CoV-2 infection. In this study, after developing a quantitative structure activity relationship analysis based on molecular topology, several macrolide antibiotics are identified as promising SARS-…
Prediction of quinolone activity against Mycobacterium avium by molecular topology and virtual computational screening.
2000
ABSTRACT We conducted a quantitative structure-activity relationship study using a database of 158 quinolones previously tested against Mycobacterium avium-M. intracellulare complex in order to develop a model capable of predicting the activity of new quinolones against the M. avium-M. intracellulare complex in vitro. Topological indices were used as structural descriptors and were related to anti- M. avium-M. intracellulare complex activity by using the linear discriminant analysis (LDA) statistical technique. The discriminant equation thus obtained correctly classified 137 of the 158 quinolones, including 37 of a test group of 44 randomly chosen compounds. This model was then applied to 2…