Cargando…
Learning Deep Representations of Cardiac Structures for 4D Cine MRI Image Segmentation through Semi-Supervised Learning
Learning good data representations for medical imaging tasks ensures the preservation of relevant information and the removal of irrelevant information from the data to improve the interpretability of the learned features. In this paper, we propose a semi-supervised model—namely, combine-all in semi...
Autores principales: | Hasan, S. M. Kamrul, Linte, Cristian A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10134910/ https://www.ncbi.nlm.nih.gov/pubmed/37125242 http://dx.doi.org/10.3390/app122312163 |
Ejemplares similares
-
Lidar–Camera Semi-Supervised Learning for Semantic Segmentation
por: Caltagirone, Luca, et al.
Publicado: (2021) -
Semi-Supervised Learning in Medical MRI Segmentation: Brain Tissue with White Matter Hyperintensity Segmentation Using FLAIR MRI
por: Rieu, ZunHyan, et al.
Publicado: (2021) -
Deep echocardiography: data-efficient supervised and semi-supervised deep learning towards automated diagnosis of cardiac disease
por: Madani, Ali, et al.
Publicado: (2018) -
Semi-supervised learning /
Publicado: (2010) -
Industrial Semi-Supervised Dynamic Soft-Sensor Modeling Approach Based on Deep Relevant Representation Learning
por: Moreira de Lima, Jean Mário, et al.
Publicado: (2021)