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Title:

Placenta segmentation in ultrasound imaging: Addressing sources of uncertainty and limited field-of-view.

Document type:
Journal Article
Author(s):
Zimmer, Veronika A; Gomez, Alberto; Skelton, Emily; Wright, Robert; Wheeler, Gavin; Deng, Shujie; Ghavami, Nooshin; Lloyd, Karen; Matthew, Jacqueline; Kainz, Bernhard; Rueckert, Daniel; Hajnal, Joseph V; Schnabel, Julia A
Abstract:
Automatic segmentation of the placenta in fetal ultrasound (US) is challenging due to the (i) high diversity of placenta appearance, (ii) the restricted quality in US resulting in highly variable reference annotations, and (iii) the limited field-of-view of US prohibiting whole placenta assessment at late gestation. In this work, we address these three challenges with a multi-task learning approach that combines the classification of placental location (e.g., anterior, posterior) and semantic pl...     »
Journal title abbreviation:
Med Image Anal
Year:
2023
Journal volume:
83
Fulltext / DOI:
doi:10.1016/j.media.2022.102639
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/36257132
Print-ISSN:
1361-8415
TUM Institution:
Institut für KI und Informatik in der Medizin
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