Cargando…
Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural Networks
In this paper, we present our system for the RSNA Intracranial Hemorrhage Detection challenge, which is based on the RSNA 2019 Brain CT Hemorrhage dataset. The proposed system is based on a lightweight deep neural network architecture composed of a convolutional neural network (CNN) that takes as in...
Autores principales: | Burduja, Mihail, Ionescu, Radu Tudor, Verga, Nicolae |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582288/ https://www.ncbi.nlm.nih.gov/pubmed/33019508 http://dx.doi.org/10.3390/s20195611 |
Ejemplares similares
-
A deep learning algorithm for automatic detection and classification of acute intracranial hemorrhages in head CT scans
por: Wang, Xiyue, et al.
Publicado: (2021) -
Benefits of Low-Dose CT Scan of Head for Patients With Intracranial Hemorrhage
por: Wu, Dan, et al.
Publicado: (2020) -
Evaluation of grouped capsule network for intracranial hemorrhage segmentation in CT scans
por: Wang, Lingying, et al.
Publicado: (2023) -
Label-efficient deep semantic segmentation of intracranial hemorrhages in CT-scans
por: Spahr, Antoine, et al.
Publicado: (2023) -
Corrigendum to “Benefits of Low-Dose CT Scan of Head for Patients with Intracranial Hemorrhage”
Publicado: (2021)