Cargando…
Automatic Contour Refinement for Deep Learning Auto-segmentation of Complex Organs in MRI-guided Adaptive Radiation Therapy
PURPOSE: Fast and accurate auto-segmentation on daily images is essential for magnetic resonance imaging (MRI)–guided adaptive radiation therapy (ART). However, the state-of-the-art auto-segmentation based on deep learning still has limited success, particularly for complex structures in the abdomen...
Autores principales: | Ding, Jie, Zhang, Ying, Amjad, Asma, Xu, Jiaofeng, Thill, Daniel, Li, X. Allen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9280040/ https://www.ncbi.nlm.nih.gov/pubmed/35847549 http://dx.doi.org/10.1016/j.adro.2022.100968 |
Ejemplares similares
-
Deep learning auto-segmentation on multi-sequence magnetic resonance images for upper abdominal organs
por: Amjad, Asma, et al.
Publicado: (2023) -
The clinical evaluation of atlas-based auto-segmentation for automatic contouring during cervical cancer radiotherapy
por: Li, Yi, et al.
Publicado: (2022) -
Combining natural and artificial intelligence for robust automatic anatomy segmentation: Application in neck and thorax auto‐contouring
por: Udupa, Jayaram K., et al.
Publicado: (2022) -
Clinical Validation of Siemens’ Syngo.via Automatic Contouring System
por: Pera, Óscar, et al.
Publicado: (2023) -
Using Spatial Probability Maps to Highlight Potential Inaccuracies in Deep Learning-Based Contours: Facilitating Online Adaptive Radiation Therapy
por: van Rooij, Ward, et al.
Publicado: (2021)