Analysis of intra- and inter-observer variability in 4D liver ultrasound landmark labeling

We highlight variability in expert-labeled ground truth data for 4D ultrasound imaging and identify ultrasound artifacts as a major source of labeling inaccuracies. These findings underscore the importance of addressing observer variability and artifact-related challenges to improve the reliability of ground truth data for evaluating target tracking algorithms in 4D ultrasound applications.

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Publication Details

Journal
Journal of Medical Imaging
Published
2025-06-30
DOI
https://doi.org/10.1117/1.jmi.12.5.051807
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.36

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article

Analysis of intra- and inter-observer variability in 4D liver ultrasound landmark labeling

Daniel L. Wulff, Floris Ernst
1 citations
Journal of Medical Imaging
Radiomics and Machine Learning in Medical Imaging
1.36
article

Analysis of intra- and inter-observer variability in 4D liver ultrasound landmark labeling

Daniel L. Wulff, Floris Ernst
article en
1 citations

Abstract

We highlight variability in expert-labeled ground truth data for 4D ultrasound imaging and identify ultrasound artifacts as a major source of labeling inaccuracies. These findings underscore the importance of addressing observer variability and artifact-related challenges to improve the reliability of ground truth data for evaluating target tracking algorithms in 4D ultrasound applications.

Journal of Medical ImagingVol. 12(05)
University of Rostock (DE), University of Lübeck (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 18%
Radiomics and Machine Learning in Medical Imaging
1.36
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