Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010179
S. Roldán-Vasco
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.
{"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}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010163
Lizeth Sofia Fontalvo, Juan David Jinete Noriega, Marcelo Herrera Martínez
Electroacoustic analogies are physical modelling tools that enable the characterization of mechanical and acoustic systems. In this case, the human lung system can be characterized by this method, enabling the diagnostic and evaluation of their performance.
{"title":"Human biologic systems (lungs) modelled with electroacoustic tools in a mathemathical simulation software","authors":"Lizeth Sofia Fontalvo, Juan David Jinete Noriega, Marcelo Herrera Martínez","doi":"10.1109/STSIVA.2014.7010163","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010163","url":null,"abstract":"Electroacoustic analogies are physical modelling tools that enable the characterization of mechanical and acoustic systems. In this case, the human lung system can be characterized by this method, enabling the diagnostic and evaluation of their performance.","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":"122921666","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}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010164
Luisa F. Ramirez, A. F. Gutiérrez, J. L. Ocampo, C. Madrigal, J. Branch, A. Restrepo
This paper presents a methodology to extract correspondences on images of color patterns based on the De Bruijn sequence projected on static objects and surfaces with no specular highlights, decreasing in great number the problems with occlusions which appear with this pattern. The methodology aims to capture and process the image, the detection of changes in intensity between stripes of the pattern for each color channel R, G, B, a selective contextual algorithm and finally the comparison of neighbors to determine the similar regions. Experimental tests demonstrate that the proposed methodology identifies large number of correspondences in the images with a low error rate.
{"title":"Extraction of correspondences in color coded pattern for the 3D reconstruction using structured light","authors":"Luisa F. Ramirez, A. F. Gutiérrez, J. L. Ocampo, C. Madrigal, J. Branch, A. Restrepo","doi":"10.1109/STSIVA.2014.7010164","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010164","url":null,"abstract":"This paper presents a methodology to extract correspondences on images of color patterns based on the De Bruijn sequence projected on static objects and surfaces with no specular highlights, decreasing in great number the problems with occlusions which appear with this pattern. The methodology aims to capture and process the image, the detection of changes in intensity between stripes of the pattern for each color channel R, G, B, a selective contextual algorithm and finally the comparison of neighbors to determine the similar regions. Experimental tests demonstrate that the proposed methodology identifies large number of correspondences in the images with a low error rate.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"54 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":"121375052","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}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010165
J. Hurtado-Rincón, S. Rojas-Jaramillo, Y. Ricardo-Cespedes, A. Álvarez-Meza, G. Castellanos-Domínguez
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.
{"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}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010175
Alfredo Ocampo-Hurtado, J. A. Jaramillo-Garzón, Delio A. Aristizabal-Martinez, E. Delgado-Trejos
This paper describes the procedure for obtaining ground prospections using seismic-acoustic signals, oriented to the detection of buried objects located at the ground surface. The presented methodology uses a Helmholtz resonator as the source of perturbation and a set of omnidirectional microphones used as sensors for detecting reflections of the superficial Rayleigh waves. The results show that the methodology is able to provide ground images where the buried object can be easily detected, both in plain as well as in uneven surfaces.
{"title":"Localization of superficially buried objects by seismic-acoustic techniques","authors":"Alfredo Ocampo-Hurtado, J. A. Jaramillo-Garzón, Delio A. Aristizabal-Martinez, E. Delgado-Trejos","doi":"10.1109/STSIVA.2014.7010175","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010175","url":null,"abstract":"This paper describes the procedure for obtaining ground prospections using seismic-acoustic signals, oriented to the detection of buried objects located at the ground surface. The presented methodology uses a Helmholtz resonator as the source of perturbation and a set of omnidirectional microphones used as sensors for detecting reflections of the superficial Rayleigh waves. The results show that the methodology is able to provide ground images where the buried object can be easily detected, both in plain as well as in uneven surfaces.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"7 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":"122194953","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}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010168
Juan S. Calderon-Piedras, A. Orjuela-Cañón, David A. Sanabria-Quiroga
FastICA method has been proposed for blind identification and separation characteristics of components, this paper has made a study of this method in order to measure its performance in the task of separating real audio signals that share the same channel simultaneously. We propose an SCICA algorithm based on FastICA, which allows finding the mixing matrix and its inverse. In this way, it is possible to find representative bases, which after a clustering process, are used as impulse response filters to discriminate source signals. Parameters used in the process identifying sources are studied to improve the results.
{"title":"Blind source separation from single channel audio recording using ICA algorithms","authors":"Juan S. Calderon-Piedras, A. Orjuela-Cañón, David A. Sanabria-Quiroga","doi":"10.1109/STSIVA.2014.7010168","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010168","url":null,"abstract":"FastICA method has been proposed for blind identification and separation characteristics of components, this paper has made a study of this method in order to measure its performance in the task of separating real audio signals that share the same channel simultaneously. We propose an SCICA algorithm based on FastICA, which allows finding the mixing matrix and its inverse. In this way, it is possible to find representative bases, which after a clustering process, are used as impulse response filters to discriminate source signals. Parameters used in the process identifying sources are studied to improve the results.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"1 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":"129505644","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}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010174
J. D. Bolanos-Jojoa, J. M. Espinosa-Duran, Jaime Velasco-Medina
This work presents two efficient hardware implementations of Forward and Inverse 2D-Walsh-Hadamard Transforms that do not use memory for the transposition operation. The first one is based on wired-transposition and the second one does not require transposition. In the last case, we designed a large 1D-WHT in order to obtain a 2D transform. The architectures were completely described in VHDL and they are flexible and parameterizable from the viewpoint of the number of inputs (N) and the number of bits of each input (n). The results show that the proposed designs have a very high throughput which makes them very suitable for several image and video processing applications and embedded systems based on H.264.
{"title":"Efficient hardware design of Forward and Inverse Walsh-Hadamard transform","authors":"J. D. Bolanos-Jojoa, J. M. Espinosa-Duran, Jaime Velasco-Medina","doi":"10.1109/STSIVA.2014.7010174","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010174","url":null,"abstract":"This work presents two efficient hardware implementations of Forward and Inverse 2D-Walsh-Hadamard Transforms that do not use memory for the transposition operation. The first one is based on wired-transposition and the second one does not require transposition. In the last case, we designed a large 1D-WHT in order to obtain a 2D transform. The architectures were completely described in VHDL and they are flexible and parameterizable from the viewpoint of the number of inputs (N) and the number of bits of each input (n). The results show that the proposed designs have a very high throughput which makes them very suitable for several image and video processing applications and embedded systems based on H.264.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"12 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":"133014930","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}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010131
F. Calderon, C. Parra, Cesar L. Nino
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.
{"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}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010184
Hernán García, C. A. Torres, Hernán Darío Vargas Cardona, Mauricio A Álvarez, Á. Orozco, J. B. Padilla, Ramiro Arango
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.
{"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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：