Zobrazeno 1 - 10
of 144
pro vyhledávání: '"Ledesma-Carbayo, María J."'
Autor:
Capellán-Martín, Daniel, Jiang, Zhifan, Parida, Abhijeet, Liu, Xinyang, Lam, Van, Nisar, Hareem, Tapp, Austin, Elsharkawi, Sarah, Ledesma-Carbayo, Maria J., Anwar, Syed Muhammad, Linguraru, Marius George
Segmenting brain tumors in multi-parametric magnetic resonance imaging enables performing quantitative analysis in support of clinical trials and personalized patient care. This analysis provides the potential to impact clinical decision-making proce
Externí odkaz:
http://arxiv.org/abs/2409.08232
Autor:
Parida, Abhijeet, Capellan-Martin, Daniel, Atito, Sara, Awais, Muhammad, Ledesma-Carbayo, Maria J., Linguraru, Marius G., Anwar, Syed Muhammad
Chest X-Ray (CXR) is a widely used clinical imaging modality and has a pivotal role in the diagnosis and prognosis of various lung and heart related conditions. Conventional automated clinical diagnostic tool design strategies relying on radiology re
Externí odkaz:
http://arxiv.org/abs/2402.15534
Autor:
Capellán-Martín, Daniel, Parida, Abhijeet, Gómez-Valverde, Juan J., Sanchez-Jacob, Ramon, Roshanitabrizi, Pooneh, Linguraru, Marius G., Ledesma-Carbayo, María J., Anwar, Syed M.
Publikováno v:
21st IEEE International Symposium on Biomedical Imaging (ISBI 2024), Athens, Greece
Tuberculosis (TB) remains a significant global health challenge, with pediatric cases posing a major concern. The World Health Organization (WHO) advocates for chest X-rays (CXRs) for TB screening. However, visual interpretation by radiologists can b
Externí odkaz:
http://arxiv.org/abs/2402.14741
A Lightweight, Rapid and Efficient Deep Convolutional Network for Chest X-Ray Tuberculosis Detection
Autor:
Capellán-Martín, Daniel, Gómez-Valverde, Juan J., Bermejo-Peláez, David, Ledesma-Carbayo, María J.
Publikováno v:
2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), Cartagena, Colombia, 2023
Tuberculosis (TB) is still recognized as one of the leading causes of death worldwide. Recent advances in deep learning (DL) have shown to enhance radiologists' ability to interpret chest X-ray (CXR) images accurately and with fewer errors, leading t
Externí odkaz:
http://arxiv.org/abs/2309.02140
Autor:
Capellán-Martín, Daniel, Gómez-Valverde, Juan J., Sanchez-Jacob, Ramon, Bermejo-Peláez, David, García-Delgado, Lara, López-Varela, Elisa, Ledesma-Carbayo, Maria J.
Tuberculosis (TB) is still considered a leading cause of death and a substantial threat to global child health. Both TB infection and disease are curable using antibiotics. However, most children who die of TB are never diagnosed or treated. In clini
Externí odkaz:
http://arxiv.org/abs/2301.13786
Autor:
González, Germán, Jimenez-Carretero, Daniel, Rodríguez-López, Sara, Cano-Espinosa, Carlos, Cazorla, Miguel, Agarwal, Tanya, Agarwal, Vinit, Tajbakhsh, Nima, Gotway, Michael B., Liang, Jianming, Masoudi, Mojtaba, Eftekhari, Noushin, Saadatmand, Mahdi, Pourreza, Hamid-Reza, Fraga-Rivas, Patricia, Fraile, Eduardo, Rybicki, Frank J., Kassarjian, Ara, Estépar, Raúl San José, Ledesma-Carbayo, Maria J.
Rationale: Computer aided detection (CAD) algorithms for Pulmonary Embolism (PE) algorithms have been shown to increase radiologists' sensitivity with a small increase in specificity. However, CAD for PE has not been adopted into clinical practice, l
Externí odkaz:
http://arxiv.org/abs/2003.13440
Autor:
Danilov, Viacheslav V., Kolpashchikov, Dmitrii Yu., Gerget, Olga M., Laptev, Nikita V., Proutski, Alex, Hernández Gómez, Luis A., Alvarez, Federico, Ledesma-Carbayo, María J.
Publikováno v:
In Computerized Medical Imaging and Graphics June 2023 106
Autor:
Esteban, Oscar, Wollny, Gert, Gorthi, Subrahmanyam, Ledesma-Carbayo, Maria-J., Thiran, Jean-Philippe, Santos, Andres, Bach-Cuadra, Meritxell
Publikováno v:
Comput. Meth. Prog. Bio. 115(2):76-94 (2014)
We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multi-channel bias field correction based on a B-spline model. A second methodological n
Externí odkaz:
http://arxiv.org/abs/1404.0600
Akademický článek
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Autor:
Jimenez-Carretero, Daniel, Bermejo-Peláez, David, Nardelli, Pietro, Fraga, Patricia, Fraile, Eduardo, San José Estépar, Raúl, Ledesma-Carbayo, Maria J
Publikováno v:
In Medical Image Analysis February 2019 52:144-159