Cargando…
Automatic Fetal Middle Sagittal Plane Detection in Ultrasound Using Generative Adversarial Network
Background and Objective: In the first trimester of pregnancy, fetal growth, and abnormalities can be assessed using the exact middle sagittal plane (MSP) of the fetus. However, the ultrasound (US) image quality and operator experience affect the accuracy. We present an automatic system that enables...
Autores principales: | Tsai, Pei-Yin, Hung, Ching-Hui, Chen, Chi-Yeh, Sun, Yung-Nien |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7824131/ https://www.ncbi.nlm.nih.gov/pubmed/33374307 http://dx.doi.org/10.3390/diagnostics11010021 |
Ejemplares similares
-
Generative Adversarial Networks to Improve Fetal Brain Fine-Grained Plane Classification
por: Montero, Alberto, et al.
Publicado: (2021) -
Artificial Intelligence for Automatic Measurement of Sagittal Vertical Axis Using ResUNet Framework
por: Weng, Chi-Hung, et al.
Publicado: (2019) -
Automatic Recognition of Fetal Facial Standard Plane in Ultrasound Image via Fisher Vector
por: Lei, Baiying, et al.
Publicado: (2015) -
Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes
por: Burgos-Artizzu, Xavier P., et al.
Publicado: (2020) -
Reproducibility and Reliability of Dynamic Ultrasound for Evaluating Tibiofibular Translation in the Sagittal Plane
por: Hagemeijer, Noortje, et al.
Publicado: (2019)