Cargando…
Convolutional Neural Networks to Detect Vestibular Schwannomas on Single MRI Slices: A Feasibility Study
SIMPLE SUMMARY: Due to the fact that they take inter-slice information into account, 3D- and 2.5D-convolutional neural networks (CNNs) potentially perform better in tumor detection tasks than 2D-CNNs. However, this potential benefit is at the expense of increased computational power and the need for...
Autores principales: | Koechli, Carole, Vu, Erwin, Sager, Philipp, Näf, Lukas, Fischer, Tim, Putora, Paul M., Ehret, Felix, Fürweger, Christoph, Schröder, Christina, Förster, Robert, Zwahlen, Daniel R., Muacevic, Alexander, Windisch, Paul |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104481/ https://www.ncbi.nlm.nih.gov/pubmed/35565199 http://dx.doi.org/10.3390/cancers14092069 |
Ejemplares similares
-
Convolutional Neural Networks for Classifying Laterality of Vestibular Schwannomas on Single MRI Slices—A Feasibility Study
por: Sager, Philipp, et al.
Publicado: (2021) -
Longitudinal Changes of Quality of Life and Hearing Following Radiosurgery for Vestibular Schwannoma
por: Windisch, Paul, et al.
Publicado: (2021) -
Classifying the Acquisition Sequence for Brain MRIs Using Neural Networks on Single Slices
por: Braeker, Norbert, et al.
Publicado: (2022) -
Clinical Results After Single-fraction Radiosurgery for 1,002 Vestibular Schwannomas
por: Windisch, Paul Y, et al.
Publicado: (2019) -
Machine Learning for the Detection and Segmentation of Benign Tumors of the Central Nervous System: A Systematic Review
por: Windisch, Paul, et al.
Publicado: (2022)