Cargando…
Application of Spectral Algorithm Applied to Spatially Registered Bi-Parametric MRI to Predict Prostate Tumor Aggressiveness: A Pilot Study
Background: Current prostate cancer evaluation can be inaccurate and burdensome. Quantitative evaluation of Magnetic Resonance Imaging (MRI) sequences non-invasively helps prostate tumor assessment. However, including Dynamic Contrast Enhancement (DCE) in the examined MRI sequence set can add compli...
Autores principales: | Mayer, Rulon, Turkbey, Baris, Choyke, Peter L., Simone, Charles B. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297157/ https://www.ncbi.nlm.nih.gov/pubmed/37370903 http://dx.doi.org/10.3390/diagnostics13122008 |
Ejemplares similares
-
Relationship between Eccentricity and Volume Determined by Spectral Algorithms Applied to Spatially Registered Bi-Parametric MRI and Prostate Tumor Aggressiveness: A Pilot Study
por: Mayer, Rulon, et al.
Publicado: (2023) -
Assessing and testing anomaly detection for finding prostate cancer in spatially registered multi-parametric MRI
por: Mayer, Rulon, et al.
Publicado: (2023) -
Pilot study for generating and assessing nomograms and decision curves analysis to predict clinically significant prostate cancer using only spatially registered multi-parametric MRI
por: Mayer, Rulon, et al.
Publicado: (2023) -
Prediction of Prostate Cancer Disease Aggressiveness Using Bi-Parametric Mri Radiomics
por: Rodrigues, Ana, et al.
Publicado: (2021) -
The Role of MRI in Prostate Cancer Active Surveillance
por: Johnson, Linda M., et al.
Publicado: (2014)