JOM KITA KE POLITEKNIK

End-to-end First Trimester Fetal Ultrasound Video Automated CRL and NT Segmentation (Record no. 2064)

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Personal name Yasrab, Robail
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9 (RLIN) 2275
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Title End-to-end First Trimester Fetal Ultrasound Video Automated CRL and NT Segmentation
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Date of publication, distribution, etc. 2022-04-28.
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General note /pmc/articles/PMC7614066/
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General note /pubmed/36643819
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Summary, etc. This study presents a novel approach to automatic detection and segmentation of the Crown Rump Length (CRL) and Nuchal Translucency (NT), two essential measurements in the first trimester US scan. The proposed method automatically localises a standard plane within a video clip as defined by the UK Fetal Abnormality Screening Programme. A Nested Hourglass (NHG) based network performs semantic pixel-wise segmentation to extract NT and CRL structures. Our results show that the NHG network is faster (19.52% < GFlops than FCN32) and offers high pixel agreement (mean-IoU=80.74) with expert manual annotations.
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Language note en
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Topical term or geographic name as entry element Article
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Genre/form data or focus term Text
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Personal name Fu, Zeyu
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9 (RLIN) 2276
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Personal name Drukker, Lior
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Personal name Lee, Lok Hin
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Personal name Zhao, He
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Personal name Papageorghiou, Aris T.
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Personal name Noble, Alison J.
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Note Proc IEEE Int Symp Biomed Imaging
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Uniform Resource Identifier <a href="http://dx.doi.org/10.1109/ISBI52829.2022.9761400">http://dx.doi.org/10.1109/ISBI52829.2022.9761400</a>
Public note Connect to this object online.

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