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Titel:

CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy.

Dokumenttyp:
Journal Article
Autor(en):
Qiao, Mengyun; Wang, Shuo; Qiu, Huaqi; de Marvao, Antonio; O'Regan, Declan P; Rueckert, Daniel; Bai, Wenjia
Abstract:
Two key questions in cardiac image analysis are to assess the anatomy and motion of the heart from images; and to understand how they are associated with non-imaging clinical factors such as gender, age and diseases. While the first question can often be addressed by image segmentation and motion tracking algorithms, our capability to model and answer the second question is still limited. In this work, we propose a novel conditional generative model to describe the 4D spatio-temporal anatomy of...     »
Zeitschriftentitel:
IEEE Trans Med Imaging
Jahr:
2024
Band / Volume:
43
Heft / Issue:
3
Seitenangaben Beitrag:
1259-1269
Volltext / DOI:
doi:10.1109/TMI.2023.3331982
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/37948142
Print-ISSN:
0278-0062
TUM Einrichtung:
Institut für KI und Informatik in der Medizin (Prof. Rückert)
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