Deep learning architectures for the analysis and classification of brain tumors in MR images

The need to make timely and accurate diagnoses of brain diseases has posed challenges to computer-aided diagnosis systems. In this field, advances in deep learning techniques play an important role, as they carry out processes to extract relevant anatomical and functional characteristics of the tiss...

Full description

Autores:

Osorio-Barone, A.
Contreras Ortiz, Sonia Helena

Tipo de recurso:

Fecha de publicación:

2020

Institución:

Universidad Tecnológica de Bolívar

Repositorio:

Repositorio Institucional UTB

Idioma:

eng

OAI Identifier:

oai:repositorio.utb.edu.co:20.500.12585/9955

Acceso en línea:

https://hdl.handle.net/20.500.12585/9955
https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11583/115830B/Deep-learning-architectures-for-the-analysis-and-classification-of-brain/10.1117/12.2579618.short?SSO=1

Palabra clave:

Bioinformatics
Brain
Computer aided diagnosis
Convolutional neural networks
Image classification
Image enhancement
Learning systems
Magnetic resonance
Magnetic resonance imaging
Network architecture
Transfer learning
Tumors
LEMB

Rights

closedAccess

License

http://purl.org/coar/access_right/c_14cb