Cargando…
Multi-Branch Attention Learning for Bone Age Assessment with Ambiguous Label
Bone age assessment (BAA) is a typical clinical technique for diagnosing endocrine and metabolic diseases in children’s development. Existing deep learning-based automatic BAA models are trained on the Radiological Society of North America dataset (RSNA) from Western populations. However, due to the...
Autores principales: | He, Bishi, Xu, Zhe, Zhou, Dong, Chen, Yuanjiao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10221871/ https://www.ncbi.nlm.nih.gov/pubmed/37430748 http://dx.doi.org/10.3390/s23104834 |
Ejemplares similares
-
Ambiguity produces attention shifts in category learning
por: Vadillo, Miguel A., et al.
Publicado: (2016) -
The Role of Attention in Ambiguous Reversals of Structure-From-Motion
por: Stonkute, Solveiga, et al.
Publicado: (2012) -
Decoding covert shifts of attention induced by ambiguous visuospatial cues
por: Trachel, Romain E., et al.
Publicado: (2015) -
Ambiguous Results When Using the Ambiguous-Cue Paradigm to Assess Learning and Cognitive Bias in Gorillas and a Black Bear
por: McGuire, Molly C., et al.
Publicado: (2017) -
Label recovery and label correlation co-learning for multi-view multi-label classification with incomplete labels
por: He, Zhi-Fen, et al.
Publicado: (2022)