Cargando…
Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study
OBJECTIVES: Digital breast tomosynthesis (DBT) increases sensitivity of mammography and is increasingly implemented in breast cancer screening. However, the large volume of images increases the risk of reading errors and reading time. This study aims to investigate whether the accuracy of breast rad...
Autores principales: | van Winkel, Suzanne L., Rodríguez-Ruiz, Alejandro, Appelman, Linda, Gubern-Mérida, Albert, Karssemeijer, Nico, Teuwen, Jonas, Wanders, Alexander J. T., Sechopoulos, Ioannis, Mann, Ritse M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8523448/ https://www.ncbi.nlm.nih.gov/pubmed/33948701 http://dx.doi.org/10.1007/s00330-021-07992-w |
Ejemplares similares
-
New reconstruction algorithm for digital breast tomosynthesis: better
image quality for humans and computers
por: Rodriguez-Ruiz, Alejandro, et al.
Publicado: (2017) -
One-view digital breast tomosynthesis as a stand-alone modality for breast cancer detection: do we need more?
por: Rodriguez-Ruiz, Alejandro, et al.
Publicado: (2017) -
Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study
por: Rodriguez-Ruiz, Alejandro, et al.
Publicado: (2019) -
Evaluation of reader performance during interpretation of breast cancer screening: the Recall and detection Of breast Cancer in Screening (ROCS) trial study design
por: Sechopoulos, Ioannis, et al.
Publicado: (2022) -
Using deep learning to assist readers during the arbitration process: a lesion-based retrospective evaluation of breast cancer screening performance
por: Kerschke, Laura, et al.
Publicado: (2021)