Daniel U. Campos Delgado - Academia.edu (original) (raw)

Papers by Daniel U. Campos Delgado

Robotica, 2004

This paper presents an adaptive impedance control scheme for an nnn-link constrained rigid robot ... more This paper presents an adaptive impedance control scheme for an nnn-link constrained rigid robot manipulator without using the regressor. In addition, inversion of the estimated inertia matrix is also avoided and the new design is free from end-point acceleration measurements. The dynamics of the robot manipulator is assumed that all of the matrices in robot model are unavailable. Since these matrices are time-varying and their variation bounds are not given, traditional adaptive or robust designs do not apply. The function approximation technique is used here to represent uncertainties in some finite linear combinations of the orthogonal basis. The dynamics of the output tracking can thus be proved to be a stable first order filter driven by function approximation errors. Using the Lyapunov stability theory, a set of update laws is derived to give closed loop stability with proper tracking performance. A 2 DOF planar robot with environment constraint is used in the computer simulat...

2022 25th Euromicro Conference on Digital System Design (DSD)

IFMBE Proceedings, Oct 24, 2022

Composites Part B: Engineering

2016 IEEE 12th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2016

In this paper, we analyze the first-order (FO) statistics of two new geometry-based statistical m... more In this paper, we analyze the first-order (FO) statistics of two new geometry-based statistical models for small-scale nonstationary time-frequency (TF) dispersive mobile-to-mobile (M2M) fading channels. We derive exact analytic expressions for the joint and marginal probability density functions (PDFs) of the envelope and phase of both models. In addition, we analyze the asymptotic behavior of these PDFs as the number of multipath components of the received signal approaches infinity. The obtained results are of practical relevance, as they can be used as a benchmark to investigate the influence of the small-scale fading statistics of nonstationary channels on the M2M communication systems' performance.

2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2013

This work is part of a continuous effort to achieve characterization of tissue from auto-fluoresc... more This work is part of a continuous effort to achieve characterization of tissue from auto-fluorescence measurements. One particular problem is the estimation of the number of components in a sample from multi-spectral Fluorescence Lifetime Imaging Data (m-FLIM). The proposed method is based on a two-step iterative procedure, where first a blind end-member and abundance extraction algorithm is employed, followed by an evaluation of the resulting end-members by solving an optimal approximation problem. A threshold method is employed to evaluate if the extracted end-members are nonredundant. The validation of the proposal is performed by 3 m-FLIM data sets from post-mortem human coronary artery samples, where the results obtained matched the qualitative description provided by histopathology slides.

Medical Imaging 2018: Computer-Aided Diagnosis, 2018

In brain cancer surgery, it is critical to achieve extensive resection without compromising adjac... more In brain cancer surgery, it is critical to achieve extensive resection without compromising adjacent healthy, noncancerous regions. Various technological advances have made major contributions in imaging, including intraoperative magnetic imaging (MRI) and computed tomography (CT). However, these technologies have pros and cons in providing quantitative, real-time and three-dimensional (3D) continuous guidance in brain cancer detection. Optical Coherence Tomography (OCT) is a non-invasive, label-free, cost-effective technique capable of imaging tissue in three dimensions and real time. The purpose of this study is to reliably and efficiently discriminate between non-cancer and cancerinfiltrated brain regions using OCT images. To this end, a mathematical model for quantitative evaluation known as the Blind End-Member and Abundances Extraction method (BEAE). This BEAE method is a constrained optimization technique which extracts spatial information from volumetric OCT images. Using this novel method, we are able to discriminate between cancerous and non-cancerous tissues and using logistic regression as a classifier for automatic brain tumor margin detection. Using this technique, we are able to achieve excellent performance using an extensive cross-validation of the training dataset (sensitivity 92.91% and specificity 98.15%) and again using an independent, blinded validation dataset (sensitivity 92.91% and specificity 86.36%). In summary, BEAE is well-suited to differentiate brain tissue which could support the guiding surgery process for tissue resection.

2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021

Blind linear unmixing (BLU) methods allow the separation of multi and hyperspectral data into end... more Blind linear unmixing (BLU) methods allow the separation of multi and hyperspectral data into end-members and abundance maps in an unsupervised fashion. However, due to incident noise, the abundance maps can exhibit high presence of granularity. To address this problem, in this paper, we present a novel proposal for BLU that considers spatial coherence in the abundance estimations, through a total spatial variation component. The proposed BLU formulation is based on the blind end-member and abundance extraction perspective with total spatial variation (EBEAE-STV). In EBEAE-STV, internal abundances are added to incorporate the spatial coherence in the cost function, which is solved by a coordinates descent algorithm. The results with synthetic data show that the proposed algorithm can significantly decrease the granularity in the estimated abundances, and the estimation errors and computational times are lower compared to state of the art methodologies. Clinical relevance-The proper and robust estimation of end-members and their respective contributions (abundances) in multi-spectral and hyper-spectral images from the proposed EBEAE-STV methodology might provide useful information in several biomedical applications, such as chemometric analysis on different biological samples, tumor identification and brain tissue classification for hyper-spectral imaging, among others.

Blind deconvolution estimation of fluorescence measurements through

2017 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), 2017

In medium and high voltage industrial applications multilevel converters are widely employed due ... more In medium and high voltage industrial applications multilevel converters are widely employed due to their capability to achieve both, high quality output voltages, as well as input currents. In particular, the neutral point clamped (NPC) converter highlights as a valuable choice. Hence, in this paper, the properties of single-phase NPC converters are studied. The analysis is focused on the active power injection property of a single-phase five level (5L-NPC) converter. The control scheme of this converter is based on a current tracking loop, which includes a proportional resonant (PR) scheme. Furthermore, the switching harmonic content is evaluated and compared to the three-level NPC (3L-NPC) counterpart. Moreover an efficiency analysis for both topologies is performed. Experimental validation in 2 kW single-phase 3L-NPC and 5L-NPC prototypes is provided to assess the performance of the controlled systems.

2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021

The Biomedical Engineering (BME) bachelor program of the Faculty of Sciences in Universidad Autón... more The Biomedical Engineering (BME) bachelor program of the Faculty of Sciences in Universidad Autónoma de San Luis Potosí (UASLP) was created in June of 2010, with the aim of training professionals with an integral perspective in the engineering field by considering a multidisciplinary approach to develop and apply technology in the areas of medicine and biology. After 10 years, our BME program has achieved national recognition. Despite of being an emerging program, this achievement has been obtained by the consolidation of our academic staff, the outstanding participation of our students in national and international academic events, and the historical graduation results. In our comprehensive evaluation, we report an overall terminal efficiency (completion rate) of 67% and a graduation rate of 47.2%, where these values are above the average for an engineering program in our institution. Additionally, the BME program provides students with solid skills and background to carry out research activities, which has resulted in a considerable number of alumni pursuing graduate studies or have already completed one. Our results show that 90% of our former students are working after graduation, but only 44% work in the field of biomedical engineering, since the regional labor market starts to saturate given the fact that, at present, students from six generations have completed our BME bachelor program. In this way, few graduates visualize the wide spectrum of job options where a biomedical engineer can impact, by their distinctive comprehensive and multidisciplinary training. Therefore, it is necessary to propose new curricular design strategies to provide our students with an academic training that allows them to enter a globalized world, where there is an even greater spectrum of engineering possibilities related to the fields of medicine and biology, in line with current trends.

2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021

Tissular blood perfusion is helpful to assess the health condition of a subject and even monitor ... more Tissular blood perfusion is helpful to assess the health condition of a subject and even monitor superficial lesions. Current state of the art is focused on developing noninvasive, quantitative and accessible methods for blood flow monitoring in large areas. This paper presents an approach based on multispectral images on the VIS-NIR range to quantify blood perfusion. Our goal is to estimate the changes in deoxygenated hemoglobin. To do so, we employ principal component analysis followed by a linear regression model. The proposal was evaluated using in-vivo data from a vascular occlusion protocol, and the results were validated against photoplethysmography measurements. Although the number of subjects in the protocol was limited, our model made a prediction with an average similarity of 91.53% with a mean R-squared adjusted of 0.8104.

2018 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), 2018

In this paper a new modulation strategy for the single-phase H-bridge neutral point clamped (HNPC... more In this paper a new modulation strategy for the single-phase H-bridge neutral point clamped (HNPC) topology is presented. The proposed modulation scheme allows the conventional five levels multilevel inverter to generate a seven levels output voltage waveform, without any changes in the structure of the HNPC topology. For this purpose a modulation scheme based on the typical Level Shift Pulse Width Modulation (LS-PWM) is designed. In order to obtain the seven output voltage levels, the DC-link is split in asymmetric form, that is one of the DC-side capacitor voltage is the double of the other one. Numerical results were obtained for a grid-tied photovoltaic system in order to evaluate the performance of the proposed modulation technique. An efficiency analysis of the proposed modulation strategy is also shown to illustrate the advantage of this scheme.

Avances recientes han permitido el desarrollo de dispositivos capaces de capturar informacion en ... more Avances recientes han permitido el desarrollo de dispositivos capaces de capturar informacion en multiples longitudes de onda. Estos datos tienen diversas aplicaciones con el problema en comun de como interpretarlos. Una de las tecnicas utilizadas con este fin es la descomposicion espectral, que separa los datos de una muestra en sus componentes basicos y concentraciones proporcionales. Nuestro trabajo previo ha estado enfocado en la descomposicion espectral de datos de fluorescencia multiespectral, donde se han desarrollado metodos que proporcionan una solucion cuantitativa, robusta y rapida, la cual no esta limitada por el numero de componentes que se pueden caracterizar. En este trabajo, presentamos una interface desarrollada en Matlab que puede estimar los perfiles caracteristicos de los componentes constituyentes de una muestra y sus abundancias. En caso de que no se tenga informacion alguna sobre la muestra, nos permite obtener ademas el numero de componentes en ella. El artic...

2020 IEEE International Conference on Industrial Technology (ICIT), 2020

This paper introduces a model-based fault detection and isolation (FDI) strategy for an open-circ... more This paper introduces a model-based fault detection and isolation (FDI) strategy for an open-circuit fault (OCF) in the power switches of a 3-phase cascaded H-bridge (CHB) converter, in the generalized case of n-levels (CHB-nL). A 3-phase shunt active power filter (SAPF) application has been considered in this work. The proposed scheme consists of two stages: the first one is fault detection, which will be in charge of indicating which phase is faulty in the CHB-nL converter, and the second one is fault isolation. The fault detection stage is implemented by a sliding-mode observer in the α -ß -coordinates based on an additive modeling perspective of the faults. The isolation stage will identify the exact failing pair of switches within the H-bridge per phase. To achieve fault isolation, proportional-integral observers are proposed to estimate the DC fault profiles. Simulation results using a 3-phase 7-levels CHB (CHB-7L) converter with N=3 bridges are presented to assess the perform...

El analisis de la respuesta al impulso de fluorescencia usando componentes exponenciales provee d... more El analisis de la respuesta al impulso de fluorescencia usando componentes exponenciales provee de informacion que permite caracterizar cuantitativamente sistemas biologicos Sin embargo, usando metodos tradicionales de deconvolucion se tiene la problematica de que la respuesta del instrumento o entrada del sistema puede no estar disponible o tiene que ser medida fuera de linea, lo que provoca un problema de sincronizacion. Por lo que en este trabajo, se propone una metodologia iterativa para resolver el problema de deconvolucion de forma ciega, es decir estimando simultaneamente la respuesta del instrumento y las respuestas al impulso fluorescentes de forma simultanea, lo cual realizamos partiendo de un conjunto de mediciones de imagenologia microscopica de fluorescencia de tiempo de vida. En nuestra formulacion se emplea una base conformada por funciones de Laguerre para expandir la respuesta al impulso fluorescente. El metodo de deconvolucion ciega propuesto es formulado como un p...

Applied Sciences, 2020

Hyperspectral imaging is a multidimensional optical technique with the potential of providing fas... more Hyperspectral imaging is a multidimensional optical technique with the potential of providing fast and accurate tissue classification. The main challenge is the adequate processing of the multidimensional information usually linked to long processing times and significant computational costs, which require expensive hardware. In this study, we address the problem of tissue classification for intraoperative hyperspectral images of in vivo brain tissue. For this goal, two methodologies are introduced that rely on a blind linear unmixing (BLU) scheme for practical tissue classification. Both methodologies identify the characteristic end-members related to the studied tissue classes by BLU from a training dataset and classify the pixels by a minimum distance approach. The proposed methodologies are compared with a machine learning method based on a supervised support vector machine (SVM) classifier. The methodologies based on BLU achieve speedup factors of ~459× and ~429× compared to th...

Robotica, 2004

This paper presents an adaptive impedance control scheme for an nnn-link constrained rigid robot ... more This paper presents an adaptive impedance control scheme for an nnn-link constrained rigid robot manipulator without using the regressor. In addition, inversion of the estimated inertia matrix is also avoided and the new design is free from end-point acceleration measurements. The dynamics of the robot manipulator is assumed that all of the matrices in robot model are unavailable. Since these matrices are time-varying and their variation bounds are not given, traditional adaptive or robust designs do not apply. The function approximation technique is used here to represent uncertainties in some finite linear combinations of the orthogonal basis. The dynamics of the output tracking can thus be proved to be a stable first order filter driven by function approximation errors. Using the Lyapunov stability theory, a set of update laws is derived to give closed loop stability with proper tracking performance. A 2 DOF planar robot with environment constraint is used in the computer simulat...

2022 25th Euromicro Conference on Digital System Design (DSD)

IFMBE Proceedings, Oct 24, 2022

Composites Part B: Engineering

2016 IEEE 12th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2016

In this paper, we analyze the first-order (FO) statistics of two new geometry-based statistical m... more In this paper, we analyze the first-order (FO) statistics of two new geometry-based statistical models for small-scale nonstationary time-frequency (TF) dispersive mobile-to-mobile (M2M) fading channels. We derive exact analytic expressions for the joint and marginal probability density functions (PDFs) of the envelope and phase of both models. In addition, we analyze the asymptotic behavior of these PDFs as the number of multipath components of the received signal approaches infinity. The obtained results are of practical relevance, as they can be used as a benchmark to investigate the influence of the small-scale fading statistics of nonstationary channels on the M2M communication systems' performance.

2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2013

This work is part of a continuous effort to achieve characterization of tissue from auto-fluoresc... more This work is part of a continuous effort to achieve characterization of tissue from auto-fluorescence measurements. One particular problem is the estimation of the number of components in a sample from multi-spectral Fluorescence Lifetime Imaging Data (m-FLIM). The proposed method is based on a two-step iterative procedure, where first a blind end-member and abundance extraction algorithm is employed, followed by an evaluation of the resulting end-members by solving an optimal approximation problem. A threshold method is employed to evaluate if the extracted end-members are nonredundant. The validation of the proposal is performed by 3 m-FLIM data sets from post-mortem human coronary artery samples, where the results obtained matched the qualitative description provided by histopathology slides.

Medical Imaging 2018: Computer-Aided Diagnosis, 2018

In brain cancer surgery, it is critical to achieve extensive resection without compromising adjac... more In brain cancer surgery, it is critical to achieve extensive resection without compromising adjacent healthy, noncancerous regions. Various technological advances have made major contributions in imaging, including intraoperative magnetic imaging (MRI) and computed tomography (CT). However, these technologies have pros and cons in providing quantitative, real-time and three-dimensional (3D) continuous guidance in brain cancer detection. Optical Coherence Tomography (OCT) is a non-invasive, label-free, cost-effective technique capable of imaging tissue in three dimensions and real time. The purpose of this study is to reliably and efficiently discriminate between non-cancer and cancerinfiltrated brain regions using OCT images. To this end, a mathematical model for quantitative evaluation known as the Blind End-Member and Abundances Extraction method (BEAE). This BEAE method is a constrained optimization technique which extracts spatial information from volumetric OCT images. Using this novel method, we are able to discriminate between cancerous and non-cancerous tissues and using logistic regression as a classifier for automatic brain tumor margin detection. Using this technique, we are able to achieve excellent performance using an extensive cross-validation of the training dataset (sensitivity 92.91% and specificity 98.15%) and again using an independent, blinded validation dataset (sensitivity 92.91% and specificity 86.36%). In summary, BEAE is well-suited to differentiate brain tissue which could support the guiding surgery process for tissue resection.

2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021

Blind linear unmixing (BLU) methods allow the separation of multi and hyperspectral data into end... more Blind linear unmixing (BLU) methods allow the separation of multi and hyperspectral data into end-members and abundance maps in an unsupervised fashion. However, due to incident noise, the abundance maps can exhibit high presence of granularity. To address this problem, in this paper, we present a novel proposal for BLU that considers spatial coherence in the abundance estimations, through a total spatial variation component. The proposed BLU formulation is based on the blind end-member and abundance extraction perspective with total spatial variation (EBEAE-STV). In EBEAE-STV, internal abundances are added to incorporate the spatial coherence in the cost function, which is solved by a coordinates descent algorithm. The results with synthetic data show that the proposed algorithm can significantly decrease the granularity in the estimated abundances, and the estimation errors and computational times are lower compared to state of the art methodologies. Clinical relevance-The proper and robust estimation of end-members and their respective contributions (abundances) in multi-spectral and hyper-spectral images from the proposed EBEAE-STV methodology might provide useful information in several biomedical applications, such as chemometric analysis on different biological samples, tumor identification and brain tissue classification for hyper-spectral imaging, among others.

Blind deconvolution estimation of fluorescence measurements through

2017 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), 2017

In medium and high voltage industrial applications multilevel converters are widely employed due ... more In medium and high voltage industrial applications multilevel converters are widely employed due to their capability to achieve both, high quality output voltages, as well as input currents. In particular, the neutral point clamped (NPC) converter highlights as a valuable choice. Hence, in this paper, the properties of single-phase NPC converters are studied. The analysis is focused on the active power injection property of a single-phase five level (5L-NPC) converter. The control scheme of this converter is based on a current tracking loop, which includes a proportional resonant (PR) scheme. Furthermore, the switching harmonic content is evaluated and compared to the three-level NPC (3L-NPC) counterpart. Moreover an efficiency analysis for both topologies is performed. Experimental validation in 2 kW single-phase 3L-NPC and 5L-NPC prototypes is provided to assess the performance of the controlled systems.

2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021

The Biomedical Engineering (BME) bachelor program of the Faculty of Sciences in Universidad Autón... more The Biomedical Engineering (BME) bachelor program of the Faculty of Sciences in Universidad Autónoma de San Luis Potosí (UASLP) was created in June of 2010, with the aim of training professionals with an integral perspective in the engineering field by considering a multidisciplinary approach to develop and apply technology in the areas of medicine and biology. After 10 years, our BME program has achieved national recognition. Despite of being an emerging program, this achievement has been obtained by the consolidation of our academic staff, the outstanding participation of our students in national and international academic events, and the historical graduation results. In our comprehensive evaluation, we report an overall terminal efficiency (completion rate) of 67% and a graduation rate of 47.2%, where these values are above the average for an engineering program in our institution. Additionally, the BME program provides students with solid skills and background to carry out research activities, which has resulted in a considerable number of alumni pursuing graduate studies or have already completed one. Our results show that 90% of our former students are working after graduation, but only 44% work in the field of biomedical engineering, since the regional labor market starts to saturate given the fact that, at present, students from six generations have completed our BME bachelor program. In this way, few graduates visualize the wide spectrum of job options where a biomedical engineer can impact, by their distinctive comprehensive and multidisciplinary training. Therefore, it is necessary to propose new curricular design strategies to provide our students with an academic training that allows them to enter a globalized world, where there is an even greater spectrum of engineering possibilities related to the fields of medicine and biology, in line with current trends.

2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021

Tissular blood perfusion is helpful to assess the health condition of a subject and even monitor ... more Tissular blood perfusion is helpful to assess the health condition of a subject and even monitor superficial lesions. Current state of the art is focused on developing noninvasive, quantitative and accessible methods for blood flow monitoring in large areas. This paper presents an approach based on multispectral images on the VIS-NIR range to quantify blood perfusion. Our goal is to estimate the changes in deoxygenated hemoglobin. To do so, we employ principal component analysis followed by a linear regression model. The proposal was evaluated using in-vivo data from a vascular occlusion protocol, and the results were validated against photoplethysmography measurements. Although the number of subjects in the protocol was limited, our model made a prediction with an average similarity of 91.53% with a mean R-squared adjusted of 0.8104.

2018 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), 2018

In this paper a new modulation strategy for the single-phase H-bridge neutral point clamped (HNPC... more In this paper a new modulation strategy for the single-phase H-bridge neutral point clamped (HNPC) topology is presented. The proposed modulation scheme allows the conventional five levels multilevel inverter to generate a seven levels output voltage waveform, without any changes in the structure of the HNPC topology. For this purpose a modulation scheme based on the typical Level Shift Pulse Width Modulation (LS-PWM) is designed. In order to obtain the seven output voltage levels, the DC-link is split in asymmetric form, that is one of the DC-side capacitor voltage is the double of the other one. Numerical results were obtained for a grid-tied photovoltaic system in order to evaluate the performance of the proposed modulation technique. An efficiency analysis of the proposed modulation strategy is also shown to illustrate the advantage of this scheme.

Avances recientes han permitido el desarrollo de dispositivos capaces de capturar informacion en ... more Avances recientes han permitido el desarrollo de dispositivos capaces de capturar informacion en multiples longitudes de onda. Estos datos tienen diversas aplicaciones con el problema en comun de como interpretarlos. Una de las tecnicas utilizadas con este fin es la descomposicion espectral, que separa los datos de una muestra en sus componentes basicos y concentraciones proporcionales. Nuestro trabajo previo ha estado enfocado en la descomposicion espectral de datos de fluorescencia multiespectral, donde se han desarrollado metodos que proporcionan una solucion cuantitativa, robusta y rapida, la cual no esta limitada por el numero de componentes que se pueden caracterizar. En este trabajo, presentamos una interface desarrollada en Matlab que puede estimar los perfiles caracteristicos de los componentes constituyentes de una muestra y sus abundancias. En caso de que no se tenga informacion alguna sobre la muestra, nos permite obtener ademas el numero de componentes en ella. El artic...

2020 IEEE International Conference on Industrial Technology (ICIT), 2020

This paper introduces a model-based fault detection and isolation (FDI) strategy for an open-circ... more This paper introduces a model-based fault detection and isolation (FDI) strategy for an open-circuit fault (OCF) in the power switches of a 3-phase cascaded H-bridge (CHB) converter, in the generalized case of n-levels (CHB-nL). A 3-phase shunt active power filter (SAPF) application has been considered in this work. The proposed scheme consists of two stages: the first one is fault detection, which will be in charge of indicating which phase is faulty in the CHB-nL converter, and the second one is fault isolation. The fault detection stage is implemented by a sliding-mode observer in the α -ß -coordinates based on an additive modeling perspective of the faults. The isolation stage will identify the exact failing pair of switches within the H-bridge per phase. To achieve fault isolation, proportional-integral observers are proposed to estimate the DC fault profiles. Simulation results using a 3-phase 7-levels CHB (CHB-7L) converter with N=3 bridges are presented to assess the perform...

El analisis de la respuesta al impulso de fluorescencia usando componentes exponenciales provee d... more El analisis de la respuesta al impulso de fluorescencia usando componentes exponenciales provee de informacion que permite caracterizar cuantitativamente sistemas biologicos Sin embargo, usando metodos tradicionales de deconvolucion se tiene la problematica de que la respuesta del instrumento o entrada del sistema puede no estar disponible o tiene que ser medida fuera de linea, lo que provoca un problema de sincronizacion. Por lo que en este trabajo, se propone una metodologia iterativa para resolver el problema de deconvolucion de forma ciega, es decir estimando simultaneamente la respuesta del instrumento y las respuestas al impulso fluorescentes de forma simultanea, lo cual realizamos partiendo de un conjunto de mediciones de imagenologia microscopica de fluorescencia de tiempo de vida. En nuestra formulacion se emplea una base conformada por funciones de Laguerre para expandir la respuesta al impulso fluorescente. El metodo de deconvolucion ciega propuesto es formulado como un p...

Applied Sciences, 2020

Hyperspectral imaging is a multidimensional optical technique with the potential of providing fas... more Hyperspectral imaging is a multidimensional optical technique with the potential of providing fast and accurate tissue classification. The main challenge is the adequate processing of the multidimensional information usually linked to long processing times and significant computational costs, which require expensive hardware. In this study, we address the problem of tissue classification for intraoperative hyperspectral images of in vivo brain tissue. For this goal, two methodologies are introduced that rely on a blind linear unmixing (BLU) scheme for practical tissue classification. Both methodologies identify the characteristic end-members related to the studied tissue classes by BLU from a training dataset and classify the pixels by a minimum distance approach. The proposed methodologies are compared with a machine learning method based on a supervised support vector machine (SVM) classifier. The methodologies based on BLU achieve speedup factors of ~459× and ~429× compared to th...