Publisher DOI: | 10.1117/12.2580720 | Title: | Tailored methods for segmentation of intravascular ultrasound images via convolutional neural networks | Language: | English | Authors: | Bargsten, Lennart Riedl, Katharina A. Wissel, Tobias Brunner, Fabian J. Schaefers, Klaus Sprenger, Johanna Grass, Michael Seiffert, Moritz Blankenberg, Stefan Schlaefer, Alexander |
Editor: | Ruiter, Nicole V. Byram, Brett C. |
Issue Date: | 2021 | Publisher: | SPIE | Source: | Ultrasonic Imaging and Tomography: SPIE Medical Imaging (2021) | Conference: | SPIE Medical Imaging, 2021 | URI: | http://hdl.handle.net/11420/8980 | ISBN: | 978-1-5106-4033-7 978-1-5106-4034-4 |
Institute: | Medizintechnische und Intelligente Systeme E-1 | Document Type: | Chapter/Article (Proceedings) | Project: | MALEKA: Maschinelle Lernverfahren für die kariovaskuläre Bildgebung auf der Grundlage des Programms für Innovation (PROFI) - Modul PROFI Transfer Plus I³-Lab - Modell-gestütztes maschinelles Lernen für die Weichgewebsmodellierung in der Medizin |
More Funding information: | European Regional Development Fund (ERDF) | Part of Series: | Volume number: | 11602 |
Appears in Collections: | Publications without fulltext |
Show full item record
Page view(s)
119
Last Week
2
2
Last month
3
3
checked on May 30, 2023
SCOPUSTM
Citations
4
Last Week
0
0
Last month
0
0
checked on Jun 30, 2022
Google ScholarTM
Check
Add Files to Item
Note about this record
Cite this record
Export
Items in TORE are protected by copyright, with all rights reserved, unless otherwise indicated.