Prediction of locations in medical images using orthogonal neural networks
Background/Purpose: An orthogonal neural network (ONN), a new deep-learning structure for medical image localization, is developed and presented in this paper. This method is simple, efficient, and completely different from a convolution neural network (CNN). Materials and methods: The diagnostic pe...
Guardado en:
Autores principales: | Jong Soo Kim, Yongil Cho, Tae Ho Lim |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Elsevier
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/af5f88bacf6942aaa8b69e1c90fccb40 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Fully automated identification of brain abnormality from whole-body FDG-PET imaging using deep learning-based brain extraction and statistical parametric mapping
por: Wonseok Whi, et al.
Publicado: (2021) -
AI in Medical Imaging: Current and Future Status—Artificial Intelligence or Augmented Imaging?
por: Anirudh Kohli
Publicado: (2021) -
Reports in Medical Imaging
Publicado: (2009) -
Saliency-based 3D convolutional neural network for categorising common focal liver lesions on multisequence MRI
por: Shu-Hui Wang, et al.
Publicado: (2021) -
Introduction of ultrasound-based living anatomy into the medical curriculum: a survey on medical students’ perceptions
por: Pelagia Kefala-Karli, et al.
Publicado: (2021)