Zobrazeno 1 - 10
of 68
pro vyhledávání: '"Ignacio A. Illán"'
Autor:
Francisco J. Martinez-Murcia, Juan M. Górriz, Javier Ramírez, Ignacio A. Illán, Fermín Segovia, Diego Castillo-Barnes, Diego Salas-Gonzalez
Publikováno v:
Frontiers in Neuroinformatics, Vol 11 (2017)
The rise of neuroimaging in research and clinical practice, together with the development of new machine learning techniques has strongly encouraged the Computer Aided Diagnosis (CAD) of different diseases and disorders. However, these algorithms are
Externí odkaz:
https://doaj.org/article/5f97034d5e6d42cb9c53fefd52b30ac8
Autor:
Diego Castillo-Barnes, Ignacio Peis, Francisco J. Martínez-Murcia, Fermín Segovia, Ignacio A. Illán, Juan M. Górriz, Javier Ramírez, Diego Salas-Gonzalez
Publikováno v:
Frontiers in Neuroinformatics, Vol 11 (2017)
A wide range of segmentation approaches assumes that intensity histograms extracted from magnetic resonance images (MRI) have a distribution for each brain tissue that can be modeled by a Gaussian distribution or a mixture of them. Nevertheless, inte
Externí odkaz:
https://doaj.org/article/8422dffaacfd4b7db7c6df21922790f9
Autor:
Ignacio A. Illán, Carmen Jimenez-Mesa, J. Rodríguez-Rivero, D. Salas, Carlos G. Puntonet, S Carillo, Francisco Jesús Martínez-Murcia, John Suckling, FJ Leiva, Juan Manuel Górriz, Javier Ramírez, Andrés Ortiz, Fermín Segovia, Diego Castillo-Barnes
Publikováno v:
Information Fusion. 57:59-70
In the immediate future, with the increasing presence of electrical vehicles and the large increase in the use of renewable energies, it will be crucial that distribution power networks are managed, supervised and exploited in a similar way as the tr
Autor:
P. Manresa-Nebot, J. M. Gorriz, Francisco Jesús Martínez-Murcia, Ignacio A. Illán, Javier Ramírez, Fermín Segovia
Publikováno v:
2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).
Magnetic Resonance Imaging (MRI) data is frequently used to assist the diagnosis of neurodegenerative disorders such as Alzheimer's disease (AD). Traditionally, experienced clinicians visually analyzed these data, looking for the patterns that charac
Autor:
Francisco Jesús Martínez-Murcia, Ignacio A. Illán, Alberto Martín-Martín, Diego Castillo-Barnes, Javier Ramírez, Carmen Jimenez-Mesa, Juan Manuel Górriz
Publikováno v:
Digibug: Repositorio Institucional de la Universidad de Granada
Universidad de Granada (UGR)
Digibug. Repositorio Institucional de la Universidad de Granada
instname
Universidad de Granada (UGR)
Digibug. Repositorio Institucional de la Universidad de Granada
instname
The detection of Alzheimer’s Disease in its early stages is crucial for patient care and drugs development. Motivated by this fact, the neuroimaging community has extensively applied machine learning techniques to the early diagnosis problem with p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2fcfcca42aad9c92c441b319e8a12d99
http://hdl.handle.net/10481/63052
http://hdl.handle.net/10481/63052
Autor:
Diego Salas-Gonzalez, Diego Castillo-Barnes, Andrés Ortiz, Juan Manuel Górriz, Carlos G. Puntonet, Javier Ramírez, Francisco Jesús Martínez-Murcia, Fermín Segovia, Ignacio A. Illán
Publikováno v:
Journal of Neuroscience Methods. 302:47-57
Background Alzheimer's disease (AD) is the most common cause of dementia in the elderly and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) is very frequently a prodromal phase of AD, and existing studies have
Autor:
Javier Ramírez, Fermín Segovia, Manuel Gómez-Río, Juan Manuel Górriz, Francisco Jesús Martínez-Murcia, Carmen Jimenez-Mesa, Carlos G. Puntonet, David López-García, Rafael Romero-Garcia, Diego Castillo-Barnes, Diego Salas-Gonzalez, Ignacio A. Illán, Andrés Ortiz, John Suckling
Publikováno v:
Digibug. Repositorio Institucional de la Universidad de Granada
instname
Digibug: Repositorio Institucional de la Universidad de Granada
Universidad de Granada (UGR)
instname
Digibug: Repositorio Institucional de la Universidad de Granada
Universidad de Granada (UGR)
In the 1970s a novel branch of statistics emerged focusing its effort on the selection of a function for the pattern recognition problem that would fulfill a relationship between the quality of the approximation and its complexity. This theory is mai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2aa4764e60f7d64d9b7b883d8ff1295a
Autor:
Ignacio A. Illán, Javier Ramírez, Julio Ortega, Juan Manuel Górriz, Juan Luis Luque, Fermín Segovia, Diego Castillo-Barnes, Roberto Cesar Morales-Ortega, Francisco Jesús Martínez-Murcia, P. J. López, Andrés Ortiz
Publikováno v:
Understanding the Brain Function and Emotions ISBN: 9783030195908
IWINAC (1)
IWINAC (1)
Electroencephalography (EEG) signals provide an important source of information of brain activity at different areas. This information can be used to diagnose brain disorders according to different activation patterns found in controls and patients.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b0f4d0ef67b33a2287368745c04810cb
https://doi.org/10.1007/978-3-030-19591-5_36
https://doi.org/10.1007/978-3-030-19591-5_36
Autor:
Ignacio A. Illán, Francisco Jesús Martínez-Murcia, Diego Salas-Gonzalez, Diego Castillo-Barnes, Juan Manuel Górriz, Javier Ramírez, Fermín Segovia
Publikováno v:
Understanding the Brain Function and Emotions ISBN: 9783030195908
IWINAC (1)
IWINAC (1)
In recent years, the use of I\(^{[123]}\)-FP-CIT or I\(^{[123]}\)-Ioflupane SPECT images has emerged as an effective support tool for Parkinson’s Disease diagnosis. Many works in this field have consisted on comparing different images obtained from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1865b83a687614286cb9907b76c4ba33
https://doi.org/10.1007/978-3-030-19591-5_39
https://doi.org/10.1007/978-3-030-19591-5_39
Autor:
Adrian L. Breto, Radka Stoyanova, I.R. Xu, Javier Perez Matos, Jorge Zavala-Hidalgo, Ignacio A. Illán, Olmo Zavala-Romero, Rosario Romero-Centeno
Publikováno v:
Submissions to the 2019 Kidney Tumor Segmentation Challenge: KiTS19.