Cargando…
Deep Learning Approaches for Automatic Quality Assurance of Magnetic Resonance Images Using ACR Phantom
BACKGROUND: In recent years, there has been a growing trend towards utilizing Artificial Intelligence (AI) and machine learning techniques in medical imaging, including for the purpose of automating quality assurance. In this research, we aimed to develop and evaluate various deep learning-based app...
Autores principales: | Torfeh, Tarraf, Aouadi, Souha, Yoganathan, SA, Paloor, Satheesh, Hammoud, Rabih, Al-Hammadi, Noora |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10685462/ https://www.ncbi.nlm.nih.gov/pubmed/38031032 http://dx.doi.org/10.1186/s12880-023-01157-5 |
Ejemplares similares
-
Design and construction of a customizable phantom for the characterization of the three‐dimensional magnetic resonance imaging geometric distortion
por: Torfeh, Tarraf, et al.
Publicado: (2021) -
Geometric accuracy of the MR imaging techniques in the presence of motion
por: Torfeh, Tarraf, et al.
Publicado: (2018) -
MRI Reduces Variation of Contouring for Boost Clinical Target Volume in Breast Cancer Patients Without Surgical Clips in the Tumour Bed
por: Al-Hammadi, Noora, et al.
Publicado: (2017) -
Off-line magnetic resonance imaging navigation of cervix cancer brachytherapy in patients with risk factors for uterine perforation
por: Al-Hammadi, Noora Mohammed, et al.
Publicado: (2017) -
Using the ACR CT accreditation phantom for routine image quality assurance on both CT and CBCT imaging systems in a radiotherapy environment
por: Hobson, Maritza A., et al.
Publicado: (2014)