Cargando…
Fully‑automated deep‑learning segmentation of pediatric cardiovascular magnetic resonance of patients with complex congenital heart diseases
BACKGROUND: For the growing patient population with congenital heart disease (CHD), improving clinical workflow, accuracy of diagnosis, and efficiency of analyses are considered unmet clinical needs. Cardiovascular magnetic resonance (CMR) imaging offers non-invasive and non-ionizing assessment of C...
Autores principales: | Karimi-Bidhendi, Saeed, Arafati, Arghavan, Cheng, Andrew L., Wu, Yilei, Kheradvar, Arash, Jafarkhani, Hamid |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7706241/ https://www.ncbi.nlm.nih.gov/pubmed/33256762 http://dx.doi.org/10.1186/s12968-020-00678-0 |
Ejemplares similares
-
Fully automatic segmentation of heart chambers in cardiac MRI using deep learning
por: Avendi, MR, et al.
Publicado: (2016) -
Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping
por: Ghadimi, Sona, et al.
Publicado: (2021) -
Deep learning for the fully automated segmentation of the inner ear on MRI
por: Vaidyanathan, Akshayaa, et al.
Publicado: (2021) -
A Fully Automated Deep Learning Network for Brain Tumor Segmentation
por: Bangalore Yogananda, Chandan Ganesh, et al.
Publicado: (2020) -
Fully Automated Breast Density Segmentation and Classification Using Deep Learning
por: Saffari, Nasibeh, et al.
Publicado: (2020)