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Automated Cardiac Realtime MRI Evaluation

Rosauer, Philipp and Wendler, Anna Clara and Koslow, Wadim and Händeler, Angelina and Terhag, Felix and Rüttgers, Alexander and Gerlach, Darius (2022) Automated Cardiac Realtime MRI Evaluation. Wissensaustausch- Workshop Machine Learning 8, 07.-09. Nov. 2022, Jena, Deutschland.

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We introduce our workflow to tackle automated evaluation of cardiac realtime MRI. The key approach is inspired by Active Learning and consists of N steps. First a limited amount of Training Data is annotated by staff with expert knowledge in the domain of pediatric cardiology. With this data we train a UNet using nnU-Net (Isensee, et. al). We then predict semantic labels with the trained model and use various techniques to judge the quality of each prediction. With that we are able to label each predicted segmentation with high or low quality. Predictions judged as low quality ones, are then presented to the domain experts and are manually corrected by them. Then, we can add those high quality labels to the training data set and start a new iteration by training the model. When the quality of predictions of an entire data set to be analyzed is high enough, we go on to synchronize the data set by assembling volumes of specific cardiac-respiration combinations based on the semantic segmentations. Finally, we are able to compute the stroke volume at different respiratory phases and compare them. The workflow explained above is deployed as a Plugin for the Software "3D Slicer".

Item URL in elib:https://elib.dlr.de/192132/
Document Type:Conference or Workshop Item (Poster)
Title:Automated Cardiac Realtime MRI Evaluation
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Rosauer, PhilippUNSPECIFIEDhttps://orcid.org/0000-0001-9984-3013UNSPECIFIED
Wendler, Anna ClaraUNSPECIFIEDhttps://orcid.org/0000-0002-1816-8907UNSPECIFIED
Terhag, FelixUNSPECIFIEDhttps://orcid.org/0000-0001-7053-8154UNSPECIFIED
Rüttgers, AlexanderUNSPECIFIEDhttps://orcid.org/0000-0001-6347-9272UNSPECIFIED
Gerlach, DariusUNSPECIFIEDhttps://orcid.org/0000-0001-7044-6065UNSPECIFIED
Date:7 November 2022
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:Semantic Segmentation, Cardiac MRI, Realtime MRI, Deep Learning, Machine Learning, Automatic Stroke Volume, Active Learning
Event Title:Wissensaustausch- Workshop Machine Learning 8
Event Location:Jena, Deutschland
Event Type:Workshop
Event Dates:07.-09. Nov. 2022
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Tasks SISTEC
Location: Köln-Porz
Institutes and Institutions:Institute for Software Technology > High-Performance Computing
Institute of Aerospace Medicine > Cardiovascular Medicine in Aerospace
Institute for Software Technology
Deposited By: Rosauer, Philipp
Deposited On:15 Dec 2022 12:06
Last Modified:29 Mar 2023 00:53

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