Tailored methods for segmentation of intravascular ultrasound images via convolutional neural networks
Standard
Tailored methods for segmentation of intravascular ultrasound images via convolutional neural networks. / Riedl, Katharina.
In: Medical Imaging 2021: Ultrasonic Imaging and Tomography, 15.02.2021.Research output: SCORING: Contribution to journal › Other (editorial matter etc.) › Research
Harvard
Riedl, K 2021, 'Tailored methods for segmentation of intravascular ultrasound images via convolutional neural networks', Medical Imaging 2021: Ultrasonic Imaging and Tomography. https://doi.org/10.1117/12.2580720
APA
Riedl, K. (2021). Tailored methods for segmentation of intravascular ultrasound images via convolutional neural networks. Medical Imaging 2021: Ultrasonic Imaging and Tomography. https://doi.org/10.1117/12.2580720
Vancouver
Riedl K. Tailored methods for segmentation of intravascular ultrasound images via convolutional neural networks. Medical Imaging 2021: Ultrasonic Imaging and Tomography. 2021 Feb 15. https://doi.org/10.1117/12.2580720
Bibtex
@article{5f8db8c52ce349ff9f419573c6f1644b,
title = "Tailored methods for segmentation of intravascular ultrasound images via convolutional neural networks",
author = "Katharina Riedl",
year = "2021",
month = feb,
day = "15",
doi = "10.1117/12.2580720",
language = "English",
}
RIS
TY - JOUR
T1 - Tailored methods for segmentation of intravascular ultrasound images via convolutional neural networks
AU - Riedl, Katharina
PY - 2021/2/15
Y1 - 2021/2/15
U2 - 10.1117/12.2580720
DO - 10.1117/12.2580720
M3 - Other (editorial matter etc.)
ER -
