Cargando…
Does deep learning software improve the consistency and performance of radiologists with various levels of experience in assessing bi-parametric prostate MRI?
OBJECTIVE: To investigate whether commercially available deep learning (DL) software improves the Prostate Imaging-Reporting and Data System (PI-RADS) scoring consistency on bi-parametric MRI among radiologists with various levels of experience; to assess whether the DL software improves the perform...
Autores principales: | Arslan, Aydan, Alis, Deniz, Erdemli, Servet, Seker, Mustafa Ege, Zeybel, Gokberk, Sirolu, Sabri, Kurtcan, Serpil, Karaarslan, Ercan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Vienna
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10027972/ https://www.ncbi.nlm.nih.gov/pubmed/36939953 http://dx.doi.org/10.1186/s13244-023-01386-w |
Ejemplares similares
-
Anatomically guided self-adapting deep neural network for clinically significant prostate cancer detection on bi-parametric MRI: a multi-center study
por: Karagoz, Ahmet, et al.
Publicado: (2023) -
A Comparative Study of Multiparametric MRI Sequences in Measuring Prostate Cancer Index Lesion Volume
por: Bagcilar, Omer, et al.
Publicado: (2022) -
Automated LVO detection and collateral scoring on CTA using a 3D self-configuring object detection network: a multi-center study
por: Bagcilar, Omer, et al.
Publicado: (2023) -
Risk Assessment of Surgical Interventions Performed on Non-Infected Patients During COVID-19 Pandemic
por: Demiroz, Anıl, et al.
Publicado: (2020) -
Retropharyngeal calcific tendinitis: Report of two cases
por: Yaylacı, Serpil, et al.
Publicado: (2015)