Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Pertusa, Antonio"'
Autor:
Castro, Daniel C., Bustos, Aurelia, Bannur, Shruthi, Hyland, Stephanie L., Bouzid, Kenza, Wetscherek, Maria Teodora, Sánchez-Valverde, Maria Dolores, Jaques-Pérez, Lara, Pérez-Rodríguez, Lourdes, Takeda, Kenji, Salinas, José María, Alvarez-Valle, Javier, Herrero, Joaquín Galant, Pertusa, Antonio
Radiology report generation (RRG) aims to create free-text radiology reports from clinical imaging. Grounded radiology report generation (GRRG) extends RRG by including the localisation of individual findings on the image. Currently, there are no man
Externí odkaz:
http://arxiv.org/abs/2411.05085
Publikováno v:
Pattern Anal Applic 27, 69 (2024)
Medical image datasets are essential for training models used in computer-aided diagnosis, treatment planning, and medical research. However, some challenges are associated with these datasets, including variability in data distribution, data scarcit
Externí odkaz:
http://arxiv.org/abs/2401.10129
Publikováno v:
Expert Systems, 41(10), e13627 (2024)
Classifying logo images is a challenging task as they contain elements such as text or shapes that can represent anything from known objects to abstract shapes. While the current state of the art for logo classification addresses the problem as a mul
Externí odkaz:
http://arxiv.org/abs/2205.05419
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:
Vayá, Maria de la Iglesia, Saborit, Jose Manuel, Montell, Joaquim Angel, Pertusa, Antonio, Bustos, Aurelia, Cazorla, Miguel, Galant, Joaquin, Barber, Xavier, Orozco-Beltrán, Domingo, García-García, Francisco, Caparrós, Marisa, González, Germán, Salinas, Jose María
This paper describes BIMCV COVID-19+, a large dataset from the Valencian Region Medical ImageBank (BIMCV) containing chest X-ray images CXR (CR, DX) and computed tomography (CT) imaging of COVID-19+ patients along with their radiological findings and
Externí odkaz:
http://arxiv.org/abs/2006.01174
We present a framework based on neural networks to extract music scores directly from polyphonic audio in an end-to-end fashion. Most previous Automatic Music Transcription (AMT) methods seek a piano-roll representation of the pitches, that can be fu
Externí odkaz:
http://arxiv.org/abs/1910.12086
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
Autor:
Bustos, Aurelia, Pertusa, Antonio
Publikováno v:
Applied Sciences, 8(7), 2018
Interventional cancer clinical trials are generally too restrictive, and some patients are often excluded on the basis of comorbidity, past or concomitant treatments, or the fact that they are over a certain age. The efficacy and safety of new treatm
Externí odkaz:
http://arxiv.org/abs/1803.08312
Publikováno v:
Neurocomputing, vol 293, 2018, Pages 87-99
MirBot is a collaborative application for smartphones that allows users to perform object recognition. This app can be used to take a photograph of an object, select the region of interest and obtain the most likely class (dog, chair, etc.) by means
Externí odkaz:
http://arxiv.org/abs/1706.02889