Zobrazeno 1 - 10
of 117
pro vyhledávání: '"de la Iglesia Vayá, María"'
Autor:
Morell-Ortega, Sergio, Ruiz-Perez, Marina, Gadea, Marien, Vivo-Hernando, Roberto, Rubio, Gregorio, Aparici, Fernando, de la Iglesia-Vaya, Maria, Catheline, Gwenaelle, Coupé, Pierrick, Manjón, José V.
This paper introduces a novel multimodal and high-resolution human brain cerebellum lobule segmentation method. Unlike current tools that operate at standard resolution ($1 \text{ mm}^{3}$) or using mono-modal data, the proposed method improves cereb
Externí odkaz:
http://arxiv.org/abs/2401.12074
Autor:
Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L, Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, galassi, anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G, Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W, Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, Gorgolewski, Krzysztof J.
The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time.
Externí odkaz:
http://arxiv.org/abs/2309.05768
Autor:
Arteaga-Arteaga, Harold Brayan, delaPava, Melissa, Mora-Rubio, Alejandro, Bravo-Ortíz, Mario Alejandro, Alzate-Grisales, Jesus Alejandro, Arias-Garzón, Daniel, López-Murillo, Luis Humberto, Buitrago-Carmona, Felipe, Villa-Pulgarín, Juan Pablo, Mercado-Ruiz, Esteban, Orozco-Arias, Simon, Hassaballah, M., de la Iglesia-Vaya, Maria, Cardona-Morales, Oscar, Tabares-Soto, Reinel
There is a necessity to develop affordable, and reliable diagnostic tools, which allow containing the COVID-19 spreading. Machine Learning (ML) algorithms have been proposed to design support decision-making systems to assess chest X-ray images, whic
Externí odkaz:
http://arxiv.org/abs/2206.05615
Autor:
Núñez, Christian, Stephan-Otto, Christian, Roldán, Alexandra, Grasa, Eva Mª, Escartí, Mª José, Aguilar García-Iturrospe, Eduardo J., García-Martí, Gracián, de la Iglesia-Vaya, Maria, Nacher, Juan, Portella, Maria J., Corripio, Iluminada
Publikováno v:
In European Neuropsychopharmacology December 2024 89:47-55
Autor:
Saenz-Gamboa, Jhon Jairo, Domenech, Julio, Alonso-Manjarrés, Antonio, Gómez, Jon A., de la Iglesia-Vayá, Maria
One of the major difficulties in medical image segmentation is the high variability of these images, which is caused by their origin (multi-centre), the acquisition protocols (multi-parametric), as well as the variability of human anatomy, the severi
Externí odkaz:
http://arxiv.org/abs/2111.08712
Autor:
López-Cerdán, Adolfo, Andreu, Zoraida, Hidalgo, Marta R., Soler-Sáez, Irene, de la Iglesia-Vayá, María, Mikozami, Akiko, Guerini, Franca R., García-García, Francisco
Publikováno v:
In Neurobiology of Disease September 2024 199
Autor:
Soler-Sáez, Irene, Karz, Alcida, Hidalgo, Marta R., Gómez-Cabañes, Borja, López-Cerdán, Adolfo, Català-Senent, José F., Prutisto-Chang, Kylie, Eskow, Nicole M., Izar, Benjamin, Redmer, Torben, Kumar, Swaminathan, Davies, Michael A., de la Iglesia-Vayá, María, Hernando, Eva, García-García, Francisco
Publikováno v:
In Journal of Investigative Dermatology September 2024
Autor:
González, Germán, Bustos, Aurelia, Salinas, José María, de la Iglesia-Vaya, María, Galant, Joaquín, Cano-Espinosa, Carlos, Barber, Xavier, Orozco-Beltrán, Domingo, Cazorla, Miguel, Pertusa, Antonio
In this work we present a method for the detection of radiological findings, their location and differential diagnoses from chest x-rays. Unlike prior works that focus on the detection of few pathologies, we use a hierarchical taxonomy mapped to the
Externí odkaz:
http://arxiv.org/abs/2006.05274
Autor:
Manjón, José V., Romero, Jose E., Vivo-Hernando, Roberto, Rubio-Navarro, Gregorio, De la Iglesia-Vaya, María, Aparici-Robles, Fernando, Coupé, Pierrick
Automatic methods for measuring normalized regional brain volumes from MRI data are a key tool to help in the objective diagnostic and follow-up of many neurological diseases. To estimate such regional brain volumes, the intracranial cavity volume is
Externí odkaz:
http://arxiv.org/abs/2001.05720
Publikováno v:
Med. Image Anal., 66 (2020), 101797
We present a labeled large-scale, high resolution chest x-ray dataset for the automated exploration of medical images along with their associated reports. This dataset includes more than 160,000 images obtained from 67,000 patients that were interpre
Externí odkaz:
http://arxiv.org/abs/1901.07441