Cargando…
Bridging the gap between prostate radiology and pathology through machine learning
BACKGROUND: Prostate cancer remains the second deadliest cancer for American men despite clinical advancements. Currently, magnetic resonance imaging (MRI) is considered the most sensitive non‐invasive imaging modality that enables visualization, detection, and localization of prostate cancer, and i...
Autores principales: | Bhattacharya, Indrani, Lim, David S., Aung, Han Lin, Liu, Xingchen, Seetharaman, Arun, Kunder, Christian A., Shao, Wei, Soerensen, Simon J. C., Fan, Richard E., Ghanouni, Pejman, To'o, Katherine J., Brooks, James D., Sonn, Geoffrey A., Rusu, Mirabela |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9543295/ https://www.ncbi.nlm.nih.gov/pubmed/35633505 http://dx.doi.org/10.1002/mp.15777 |
Ejemplares similares
-
Automated detection of aggressive and indolent prostate cancer on magnetic resonance imaging
por: Seetharaman, Arun, et al.
Publicado: (2021) -
Registration of presurgical MRI and histopathology images from radical prostatectomy via RAPSODI
por: Rusu, Mirabela, et al.
Publicado: (2020) -
Multiparametric deep learning tissue signatures for a radiological biomarker of breast cancer: Preliminary results
por: Parekh, Vishwa S., et al.
Publicado: (2019) -
Computational Detection of Extraprostatic Extension of Prostate Cancer on Multiparametric MRI Using Deep Learning
por: Moroianu, Ştefania L., et al.
Publicado: (2022) -
Effect of atelectasis changes on tissue mass and dose during lung
radiotherapy
por: Guy, Christopher L., et al.
Publicado: (2016)