Cargando…
Variability and reproducibility in deep learning for medical image segmentation
Medical image segmentation is an important tool for current clinical applications. It is the backbone of numerous clinical diagnosis methods, oncological treatments and computer-integrated surgeries. A new class of machine learning algorithm, deep learning algorithms, outperforms the results of clas...
Autores principales: | Renard, Félix, Guedria, Soulaimane, Palma, Noel De, Vuillerme, Nicolas |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7426407/ https://www.ncbi.nlm.nih.gov/pubmed/32792540 http://dx.doi.org/10.1038/s41598-020-69920-0 |
Ejemplares similares
-
The Reproducibility of Deep Learning-Based Segmentation of the Prostate Gland and Zones on T2-Weighted MR Images
por: Sunoqrot, Mohammed R. S., et al.
Publicado: (2021) -
Spine Medical Image Segmentation Based on Deep Learning
por: Zhang, Qingfeng, et al.
Publicado: (2021) -
Radiomics feature reproducibility under inter-rater variability in segmentations of CT images
por: Haarburger, Christoph, et al.
Publicado: (2020) -
Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges
por: Hesamian, Mohammad Hesam, et al.
Publicado: (2019) -
Annotation-efficient deep learning for automatic medical image segmentation
por: Wang, Shanshan, et al.
Publicado: (2021)