Cargando…
A Computationally Efficient Reconstruction Algorithm for Circular Cone-Beam Computed Tomography Using Shallow Neural Networks
Circular cone-beam (CCB) Computed Tomography (CT) has become an integral part of industrial quality control, materials science and medical imaging. The need to acquire and process each scan in a short time naturally leads to trade-offs between speed and reconstruction quality, creating a need for fa...
Autores principales: | Lagerwerf, Marinus J., Pelt, Daniël M., Palenstijn, Willem Jan, Batenburg, Kees Joost |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321184/ https://www.ncbi.nlm.nih.gov/pubmed/34460532 http://dx.doi.org/10.3390/jimaging6120135 |
Ejemplares similares
-
Integration of TomoPy and the ASTRA toolbox for advanced processing and reconstruction of tomographic synchrotron data
por: Pelt, Daniël M., et al.
Publicado: (2016) -
A cone-beam X-ray computed tomography data collection designed for machine learning
por: Der Sarkissian, Henri, et al.
Publicado: (2019) -
Real-time reconstruction and visualisation towards dynamic feedback control during time-resolved tomography experiments at TOMCAT
por: Buurlage, Jan-Willem, et al.
Publicado: (2019) -
Foam-like phantoms for comparing tomography algorithms
por: Pelt, Daniël M., et al.
Publicado: (2022) -
Cone-Beam Computed Tomography in Orthodontics
por: Abdelkarim, Ahmad
Publicado: (2019)