Cargando…
Computer Aided Classification of Neuroblastoma Histological Images Using Scale Invariant Feature Transform with Feature Encoding
Neuroblastoma is the most common extracranial solid malignancy in early childhood. Optimal management of neuroblastoma depends on many factors, including histopathological classification. Although histopathology study is considered the gold standard for classification of neuroblastoma histological i...
Autores principales: | Gheisari, Soheila, Catchpoole, Daniel R., Charlton, Amanda, Melegh, Zsombor, Gradhand, Elise, Kennedy, Paul J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165255/ https://www.ncbi.nlm.nih.gov/pubmed/30154334 http://dx.doi.org/10.3390/diagnostics8030056 |
Ejemplares similares
-
Convolutional Deep Belief Network with Feature Encoding for Classification of Neuroblastoma Histological Images
por: Gheisari, Soheila, et al.
Publicado: (2018) -
Increased Efficacy of Histone Methyltransferase G9a Inhibitors Against MYCN-Amplified Neuroblastoma
por: Bellamy, Jacob, et al.
Publicado: (2020) -
A Wnt-BMP4 Signaling Axis Induces MSX and NOTCH Proteins and Promotes Growth Suppression and Differentiation in Neuroblastoma
por: Szemes, Marianna, et al.
Publicado: (2020) -
Wnt Signalling Drives Context-Dependent Differentiation or Proliferation in Neuroblastoma()
por: Szemes, Marianna, et al.
Publicado: (2018) -
Can Archival Tissue Reveal Answers to Modern Research Questions?: Computer-Aided Histological Assessment of Neuroblastoma Tumours Collected over 60 Years
por: Chetcuti, Albert, et al.
Publicado: (2014)