Cargando…
A Data-Efficient Deep Learning Strategy for Tissue Characterization via Quantitative Ultrasound: Zone Training
Deep learning (DL) powered biomedical ultrasound imaging is an emerging research field where researchers adapt the image analysis capabilities of DL algorithms to biomedical ultrasound imaging settings. A major roadblock to wider adoption of DL powered biomedical ultrasound imaging is that acquisiti...
Autores principales: | Soylu, Ufuk, Oelze, Michael L. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224776/ https://www.ncbi.nlm.nih.gov/pubmed/37027531 http://dx.doi.org/10.1109/TUFFC.2023.3245988 |
Ejemplares similares
-
Calibrating Data Mismatches in Deep Learning-Based Quantitative Ultrasound Using Setting Transfer Functions
por: Soylu, Ufuk, et al.
Publicado: (2023) -
Using an Ultrasound Tissue Phantom Model for Hybrid Training of Deep Learning Models for Shrapnel Detection
por: Hernandez-Torres, Sofia I., et al.
Publicado: (2022) -
Accurate and generalizable quantitative scoring of liver steatosis from ultrasound images via scalable deep learning
por: Li, Bowen, et al.
Publicado: (2022) -
Machine learning-enabled quantitative ultrasound techniques for tissue differentiation
por: Thomson, Hannah, et al.
Publicado: (2022) -
An efficient ptychography reconstruction strategy through fine-tuning of large pre-trained deep learning model
por: Pan, Xinyu, et al.
Publicado: (2023)