Browsing by Author "Irarrazaval Mena, Pablo"

Now showing 1 - 5 of 5
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    Algebraic Reconstruction of Source and Attenuation in SPECT Using First Scattering Measurements
    (Springer, 2018) Cueva, Evelyn; Osses Alvarado, Axel Esteban; Quintana Fresno, Juan Carlos; Tejos Núñez, Cristián Andrés; Courdurier Bettancourt Matias Alejandro; Irarrazaval Mena, Pablo
    Here we present an Algebraic Reconstruction Technique (ART) for solving the identification problem in Single Photon Emission Computed Tomography (SPECT). Traditional reconstruction for SPECT is done by finding the radiation source, nevertheless the attenuation of the surrounding tissue affects the data. In this context, ballistic and first scattering information are used to recover source and attenuation simultaneously. Both measurements are related with the Attenuated Radon Transform and a Klein-Nishina angular type dependency is considered for the scattering. The proposed ART algorithm allow us to obtain good reconstructions of both objects in a few number of iterations.
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    Estimation the Number of Speakers Based on Adaptive Wavelet Transform by Generalized Eigenvalue Decomposition and K-means Clustering
    (IEEE, 2019) Firoozabadi, Ali; Irarrazaval Mena, Pablo; Adasme, Pablo; Durney, Hugo; Olave, Miguel; Azurdia-Meza, Cesar
    The aim of this paper is estimation the number of simultaneous speakers from the overlapped speech signals. The proposed method in this paper is based on spectrum estimation with adaptive wavelet transform in combination with generalized eigenvalue decomposition (GEVD) and K-means clustering. Firstly, the spectral estimation method is implemented on all microphone signals to select the best part of signal spectrum. In following, the microphone signals are divided to different subbands by using of adaptive wavelet transform. The GEVD algorithm is implemented on each microphone pairs in different subband to estimate the room impulse response and time difference of arrival (TDOA). Finally, the K-means clustering with silhouette criteria is used to estimate the number of speakers (K value). The proposed algorithm is implemented on simulated and real data to show the superiority of the proposed method in comparison with other previous works.
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    Intake of red wine grape pomace decreased atherosclerosis, attenuated myocardial damage and increased survival in a murine model of lethal coronary heart disease
    (MDPI, 2019) Salas Perez, Francisca Lorena; Rivera Vega, Katherine Solange; Echeverria, Guadalupe; Urquiaga, Ines; Dicenta, Sara; Perez, Druso; Andia, Marcelo; Uribe, Sergio; Tejos, Cristian; Busso, Dolores; Irarrazaval Mena, Pablo; Rigotti, Attilio
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    PET Reconstruction With Non-Negativity Constraint in Projection Space: Optimization Through Hypo-Convergence
    (IEEE, 2020) Bousse, Alexandre; Courdurier Bettancourt, Matías Alejandro; Émond, Élise; Thielemans, Kris; Hutton, Brian F.; Irarrazaval Mena, Pablo; Visvikis, Dimitris
    Standard positron emission tomography (PET) reconstruction techniques are based on maximum-likelihood (ML) optimization methods, such as the maximum-likelihood expectation-maximization (MLEM) algorithm and its variations. Most methodologies rely on a positivity constraint on the activity distribution image. Although this constraint is meaningful from a physical point of view, it can be a source of bias for low-count/high-background PET, which can compromise accurate quantification. Existing methods that allow for negative values in the estimated image usually utilize a modified log-likelihood, and therefore break the data statistics. In this paper, we propose to incorporate the positivity constraint on the projections only, by approximating the (penalized) log-likelihood function by an adequate sequence of objective functions that are easily maximized without constraint. This sequence is constructed such that there is hypo-convergence (a type of convergence that allows the convergence of the maximizers under some conditions) to the original log-likelihood, hence allowing us to achieve maximization with positivity constraint on the projections using simple settings. A complete proof of convergence under weak assumptions is given. We provide results of experiments on simulated data where we compare our methodology with the alternative direction method of multipliers (ADMM) method, showing that our algorithm converges to a maximizer, which stays in the desired feasibility set, with faster convergence than ADMM. We also show that this approach reduces the bias, as compared with MLEM images, in necrotic tumors-which are characterized by cold regions surrounded by hot structures-while reconstructing similar activity values in hot regions.
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    Similar Metabolic Health in Overweight/Obese Individuals With Contrasting Metabolic Flexibility to an Oral Glucose Tolerance Test
    (FRONTIERS MEDIA SA, 2021) Fernandez Verdejo, Rodrigo Esteban; Malo Vintimilla, Maria Lorena; Gutierrez Pino, Juan; Lopez Fuenzalida, Antonio Eduardo; Olmos, Pablo; Irarrazaval Mena, Pablo; Galgani Fuentes, Jose Eduardo
    Background: Low metabolic flexibility (MetF) may be an underlying factor for metabolic health impairment. Individuals with low MetF are thus expected to have worse metabolic health than subjects with high MetF. Therefore, we aimed to compare metabolic health in individuals with contrasting MetF to an oral glucose tolerance test (OGTT).Methods: In individuals with excess body weight, we measured MetF as the change in respiratory quotient (RQ) from fasting to 1 h after ingestion of a 75-g glucose load (i.e., OGTT). Individuals were then grouped into low and high MetF (Low-MetF n = 12; High-MetF n = 13). The groups had similar body mass index, body fat, sex, age, and maximum oxygen uptake. Metabolic health markers (clinical markers, insulin sensitivity/resistance, abdominal fat, and intrahepatic fat) were compared between groups.Results: Fasting glucose, triglycerides (TG), and high-density lipoprotein (HDL) were similar between groups. So were insulin sensitivity/resistance, visceral, and intrahepatic fat. Nevertheless, High-MetF individuals had higher diastolic blood pressure, a larger drop in TG concentration during the OGTT, and a borderline significant (P = 0.05) higher Subcutaneous Adipose Tissue (SAT). Further, compared to Low-MetF, High-MetF individuals had an about 2-fold steeper slope for the relationship between SAT and fat mass index.Conclusion: Individuals with contrasting MetF to an OGTT had similar metabolic health. Yet High-MetF appears related to enhanced circulating TG clearance and enlarged subcutaneous fat.