Cargando…
Automatic intracranial abnormality detection and localization in head CT scans by learning from free-text reports
Deep learning has yielded promising results for medical image diagnosis but relies heavily on manual image annotations, which are expensive to acquire. We present Cross-DL, a cross-modality learning framework for intracranial abnormality detection and localization in head computed tomography (CT) sc...
Autores principales: | Liu, Aohan, Guo, Yuchen, Lyu, Jinhao, Xie, Jing, Xu, Feng, Lou, Xin, Yong, Jun-hai, Dai, Qionghai |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518589/ https://www.ncbi.nlm.nih.gov/pubmed/37652014 http://dx.doi.org/10.1016/j.xcrm.2023.101164 |
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) -
Relay learning: a physically secure framework for clinical multi-site deep learning
por: Bo, Zi-Hao, et al.
Publicado: (2023) -
Corrigendum to “Benefits of Low-Dose CT Scan of Head for Patients with Intracranial Hemorrhage”
Publicado: (2021) -
Serial Brain CT Scans in Severe Head Injury without Intracranial Pressure Monitoring
por: Shin, Dong-Seong, et al.
Publicado: (2014)