2014 XIX Symposium on Image, Signal Processing and Artificial Vision最新文献_第4页

Linear and non-linear autoregressive modeling in subthalamic nucleus for patients with movement disorders. Comparison and critical analysis 运动障碍患者的丘脑底核线性和非线性自回归模型。比较与批判分析

2014 XIX Symposium on Image, Signal Processing and Artificial Vision Pub Date : 2014-09-01 DOI: 10.1109/STSIVA.2014.7010179

S. Roldán-Vasco

{"title":"Linear and non-linear autoregressive modeling in subthalamic nucleus for patients with movement disorders. Comparison and critical analysis","authors":"S. Roldán-Vasco","doi":"10.1109/STSIVA.2014.7010179","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010179","url":null,"abstract":"The Deep Brain Stimulation is a surgical procedure in which an electrode is implanted, used by functional neurosurgeons to control the discharge rates of motor units (basal ganglia) in patients with movement disorders. The success of the procedure depends on exactly localization of surgical target, conventionally the subthalamic nucleus, thalamus or globus pallidus internus, which have a particular voltage profile. In this work, two kind of parametric structures, non-linear ARX and linear AR, have been used for modeling the intracerebral signals in patients with Parkinson disease. This work evaluates the fitness with both modeling techniques and their dependence of the linearity regressors and the prediction horizon. The author found that the signals without Gaussian behavior were strongly sensitive of the prediction horizon. On the other hand, both AR and NLARX had good enough precision that guarantees an accurate simulation. This work aims to establish the better modeling criteria trough an a comparison between fitness for AR and NLARX structures and the final model of subthalamic nucleus signals for an oblique coordinate system.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121617167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Human biologic systems (lungs) modelled with electroacoustic tools in a mathemathical simulation software 在数学模拟软件中用电声工具对人体生物系统(肺)进行建模

2014 XIX Symposium on Image, Signal Processing and Artificial Vision Pub Date : 2014-09-01 DOI: 10.1109/STSIVA.2014.7010163

Lizeth Sofia Fontalvo, Juan David Jinete Noriega, Marcelo Herrera Martínez

引用次数: 1

Extraction of correspondences in color coded pattern for the 3D reconstruction using structured light 利用结构光进行三维重建，提取彩色编码模式的对应关系

2014 XIX Symposium on Image, Signal Processing and Artificial Vision Pub Date : 2014-09-01 DOI: 10.1109/STSIVA.2014.7010164

Luisa F. Ramirez, A. F. Gutiérrez, J. L. Ocampo, C. Madrigal, J. Branch, A. Restrepo

引用次数: 1

Motor imagery classification using feature relevance analysis: An Emotiv-based BCI system 基于特征关联分析的运动意象分类:一个基于emotivo的脑机接口系统

2014 XIX Symposium on Image, Signal Processing and Artificial Vision Pub Date : 2014-09-01 DOI: 10.1109/STSIVA.2014.7010165

J. Hurtado-Rincón, S. Rojas-Jaramillo, Y. Ricardo-Cespedes, A. Álvarez-Meza, G. Castellanos-Domínguez

{"title":"Motor imagery classification using feature relevance analysis: An Emotiv-based BCI system","authors":"J. Hurtado-Rincón, S. Rojas-Jaramillo, Y. Ricardo-Cespedes, A. Álvarez-Meza, G. Castellanos-Domínguez","doi":"10.1109/STSIVA.2014.7010165","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010165","url":null,"abstract":"Brain Computer Interfaces (BCI) have been emerged as an alternative to support automatic systems able to interpret brain functions, commonly, by analyzing electroencephalography (EEG) recordings. In this work, a time-series discrimination methodology, called Motor Imagery Discrimination by Relevance Analysis (MIDRA), is presented to support the development of BCI from EEG data. Particularly, a Motor Imagery (MI) paradigm is studied, i.e., imagination of left-right hand movements. In this sense, a feature relevance analysis strategy is presented to select representing characteristics using a variability criterion. Besides, short-time parameters are estimated from EEG data by considering both time and time-frequency representations to deal with non-stationary dynamics. MIDRA is assessed on two different BCI databases, a well-known MI data and an Emotiv-based dataset. Attained results showed that MIDRA enhances the BCI system performance in comparison with benchmark methods by suitable ranking the input feature set. Moreover, applying MIDRA in a BCI based on the Emotiv device is a straightforward alternative for dealing with MI paradigms.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115623812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Localization of superficially buried objects by seismic-acoustic techniques 用地震声技术定位浅层埋地物体

2014 XIX Symposium on Image, Signal Processing and Artificial Vision Pub Date : 2014-09-01 DOI: 10.1109/STSIVA.2014.7010175

Alfredo Ocampo-Hurtado, J. A. Jaramillo-Garzón, Delio A. Aristizabal-Martinez, E. Delgado-Trejos

引用次数: 0

Blind source separation from single channel audio recording using ICA algorithms 利用ICA算法对单声道录音进行盲源分离

2014 XIX Symposium on Image, Signal Processing and Artificial Vision Pub Date : 2014-09-01 DOI: 10.1109/STSIVA.2014.7010168

Juan S. Calderon-Piedras, A. Orjuela-Cañón, David A. Sanabria-Quiroga

引用次数: 10

Efficient hardware design of Forward and Inverse Walsh-Hadamard transform 正、逆沃尔什-阿达玛变换的高效硬件设计

2014 XIX Symposium on Image, Signal Processing and Artificial Vision Pub Date : 2014-09-01 DOI: 10.1109/STSIVA.2014.7010174

J. D. Bolanos-Jojoa, J. M. Espinosa-Duran, Jaime Velasco-Medina

引用次数: 3

Depth map estimation in light fields using an stereo-like taxonomy 使用类似立体分类的光场深度图估计

2014 XIX Symposium on Image, Signal Processing and Artificial Vision Pub Date : 2014-09-01 DOI: 10.1109/STSIVA.2014.7010131

F. Calderon, C. Parra, Cesar L. Nino

{"title":"Depth map estimation in light fields using an stereo-like taxonomy","authors":"F. Calderon, C. Parra, Cesar L. Nino","doi":"10.1109/STSIVA.2014.7010131","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010131","url":null,"abstract":"The light field or LF is a function that describes the amount of light traveling in every direction (angular) through every point (spatial) in a scene, this LF can be captured in several ways, using arrays of cameras, or more recently using a single camera with an special lens, that allows the capture of angular and spatial information of light rays of a scene (LF). This recent camera implementation gives a different approach to find the dept of a scene using only a single camera. In order to estimate the depth, we describe a taxonomy, similar to the one used in stereo Depth-map algorithms. That consist in the creation of a cost tensor to represent the matching cost between different disparities, then, using a support weight window, aggregate the cost tensor, finally, using a winner-takes-all optimization algorithm, search for the best disparities. This paper explains in detail the several changes made to an stereo-like taxonomy, to be applied in a light field, and evaluate this algorithm using a recent database that for the first time, provides several ground-truth light fields, with a respective ground-truth depth map.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122389767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

3D brain atlas reconstruction using deformable medical image registration: Application to deep brain stimulation surgery 利用可变形医学图像配准重建三维脑图谱:在深部脑刺激手术中的应用

2014 XIX Symposium on Image, Signal Processing and Artificial Vision Pub Date : 2014-09-01 DOI: 10.1109/STSIVA.2014.7010184

Hernán García, C. A. Torres, Hernán Darío Vargas Cardona, Mauricio A Álvarez, Á. Orozco, J. B. Padilla, Ramiro Arango

{"title":"3D brain atlas reconstruction using deformable medical image registration: Application to deep brain stimulation surgery","authors":"Hernán García, C. A. Torres, Hernán Darío Vargas Cardona, Mauricio A Álvarez, Á. Orozco, J. B. Padilla, Ramiro Arango","doi":"10.1109/STSIVA.2014.7010184","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010184","url":null,"abstract":"In deep brain stimulation surgery the most important step is the correct location of the neurostimulator device. Here, the medical specialist needs to robustly locate the basal ganglia area (i.e. subthalamic nucleus) to implant the neurostim-ulator. 3D brain atlas reconstruction methods have become in useful tools for building image guide surgery systems due to the benefits for 3D brain structure location in an interactive way. In this paper we proposes a 3D brain atlas reconstruction using deformable medical image registration for applications in deep brain stimulation surgeries. To quantitatively evaluate the performance of the registration process, we vary the registration parameters such as optimizers, similarity metrics and interpolators. The experimental results shows that deformable image registration in 3D medical images can efficiently reconstructs a 3D brain atlas from volumetric data previously labeled (Brain atlas labeled for a baseline patient) and can be used in image guide surgery systems.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131555796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1