Browsing by Author "Silva, Javier"

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    Chile: On the road to global sustainable mining
    (2023) Guzman, Juan Ignacio; Karpunina, Alina; Araya, Constanza; Faundez, Patricio; Bocchetto, Marcela; Camacho, Rodolfo; Desormeaux, Daniela; Galaz, Juanita; Garces, Ingrid; Kracht, Willy; Lagos, Gustavo; Marshall, Isabel; Perez, Victor; Silva, Javier; Toro, Ignacio; Vial, Alejandra; Wood, Alejandra
    The energy transition relies heavily on minerals such as copper and lithium. In today's modern world, where consumers are increasingly aware of the need to protect tomorrow's natural resources, mining is expected to be not only economical but also socially and environmentally sustainable. In light of this, mining production must be competitive in these three dimensions of sustainability to meet demand, understanding that consumers will prefer a more sustainable material. This study aims to comprehend the competitiveness of copper and lithium Chilean production from a sustainable perspective using a SWOT analysis (Strengths, Weaknesses, Opportunities, and Threats) developed by a panel of experts.Based on an analysis of 165 factors driving mining's sustainability, the copper industry in Chile ranks third in the sustainability ranking for the world, while lithium ranks second. The foregoing implies that Chile, the world's leading producer of copper and second global producer of lithium, still has room to improve sustainability by introducing the following measures: (1) improving effective communication among stakeholders; (2) dissemi-nating sustainability knowledge; (3) developing State mining policies; (4) restoring stability in the country; (5) developing a sustainable quality brand of Chilean commodities; and (6) capitalizing on valuable human capital.
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    Toward a realistic in silico abdominal phantom for QSM
    (2023) Silva, Javier; Milovic, Carlos; Lambert Villanueva, Mathias Gabriel; Montalba Zalaquett, Cristián Andrés; Arrieta Pellegrin, Cristóbal Ignacio; Irarrázaval Mena Pablo; Uribe Arancibia, Sergio Andres; Tejos Nuñez, Cristián Andrés
    Purpose: QSM outside the brain has recently gained interest, particularly in the abdominal region. However, the absence of reliable ground truths makes difficult to assess reconstruction algorithms, whose quality is already compromised by additional signal contributions from fat, gases, and different kinds of motion. This work presents a realistic in silico phantom for the development, evaluation and comparison of abdominal QSM reconstruction algorithms. Methods: Synthetic susceptibility and R∗2𝑅2* maps were generated by segmenting and postprocessing the abdominal 3T MRI data from a healthy volunteer. Susceptibility and R∗2𝑅2* values in different tissues/organs were assigned according to literature and experimental values and were also provided with realistic textures. The signal was simulated using as input the synthetic QSM and R∗2𝑅2* maps and fat contributions. Three susceptibility scenarios and two acquisition protocols were simulated to compare different reconstruction algorithms. Results: QSM reconstructions show that the phantom allows to identify the main strengths and limitations of the acquisition approaches and reconstruction algorithms, such as in-phase acquisitions, water-fat separation methods, and QSM dipole inversion algorithms. Conclusion: The phantom showed its potential as a ground truth to evaluate and compare reconstruction pipelines and algorithms. The publicly available source code, designed in a modular framework, allows users to easily modify the susceptibility, R∗2𝑅2* and TEs, and thus creates different abdominal scenarios.
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    XSIM: A structural similarity index measure optimized for MRI QSM
    (2025) Milovic, Carlos; Tejos, Cristian; Silva, Javier; Shmueli, Karin; Irarrazaval, Pablo
    Purpose: The structural similarity index measure (SSIM) has become a popular quality metric to evaluate QSM in a way that is closer to human perception than RMS error (RMSE). However, SSIM may overpenalize errors in diamagnetic tissues and underpenalize them in paramagnetic tissues, resulting in biasing. In addition, extreme artifacts may compress the dynamic range, resulting in unrealistically high SSIM scores (hacking). To overcome biasing and hacking, we propose XSIM: SSIM implemented in the native QSM range, and with internal parameters optimized for QSM. Methods: We used forward simulations from a COSMOS ground-truth brain susceptibility map included in the 2016 QSM Reconstruction Challenge to investigate the effect of QSM reconstruction errors on the SSIM, XSIM, and RMSE metrics. We also used these metrics to optimize QSM reconstructions of the in vivo challenge data set. We repeated this experiment with the QSM abdominal phantom. To validate the use of XSIM instead of SSIM for QSM quality assessment across a range of different reconstruction techniques/algorithms, we analyzed the reconstructions submitted to the 2019 QSM Reconstruction Challenge 2.0. Results: Our experiments confirmed the biasing and hacking effects on the SSIM metric applied to QSM. The XSIM metric was robust to those effects, penalizing the presence of streaking artifacts and reconstruction errors. Using XSIM to optimize QSM reconstruction regularization weights returned less overregularization than SSIM and RMSE. Conclusion: XSIM is recommended over traditional SSIM to evaluate QSM reconstructions against a known ground truth, as it avoids biasing and hacking effects and provides a larger dynamic range of scores.