Overview of Machine Learning: Part 2: Deep Learning for Medical Image Analysis.
Neuroimaging Clin N Am
; 30(4): 417-431, 2020 Nov.
Article
en En
| MEDLINE
| ID: mdl-33038993
ABSTRACT
Deep learning has contributed to solving complex problems in science and engineering. This article provides the fundamental background required to understand and develop deep learning models for medical imaging applications. The authors review the main deep learning architectures such as multilayer perceptron, convolutional neural networks, autoencoders, recurrent neural networks, and generative adversarial neural networks. They also discuss the strategies for training deep learning models when the available datasets are imbalanced or of limited size and conclude with a discussion of the obstacles and challenges hindering the deployment of deep learning solutions in clinical settings.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Interpretación de Imagen Asistida por Computador
/
Neuroimagen
/
Aprendizaje Automático
Límite:
Humans
Idioma:
En
Revista:
Neuroimaging Clin N Am
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
/
NEUROLOGIA
Año:
2020
Tipo del documento:
Article
País de afiliación:
Canadá