Evaluating structural uncertainty in accelerated MRI: are voxelwise measures useful surrogates?
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916890881818624 |
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| author | Trautmann, Luca L. C. Wijeratne, Peter A. Ronen, Itamar Simpson, Ivor J. A. |
| author_facet | Trautmann, Luca L. C. Wijeratne, Peter A. Ronen, Itamar Simpson, Ivor J. A. |
| contents | Introducing accelerated reconstruction algorithms into clinical settings requires measures of uncertainty quantification that accurately assess the relevant uncertainty introduced by the reconstruction algorithm. Many currently deployed approaches quantifying uncertainty by focusing on measuring the variability in voxelwise intensity variation. Although these provide interpretable maps, they lack a structural interpretation and do not show a clear relationship to how the data will be analysed subsequently. In this work we show that voxel level uncertainty does not provide insight into morphological uncertainty. To do so, we use segmentation as a clinically-relevant downstream task and deploy ensembles of reconstruction modes to measure uncertainty in the reconstructions. We show that variability and bias in the morphological structures are present and within-ensemble variability cannot be predicted well with uncertainty measured only by voxel intensity variations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_10527 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Evaluating structural uncertainty in accelerated MRI: are voxelwise measures useful surrogates? Trautmann, Luca L. C. Wijeratne, Peter A. Ronen, Itamar Simpson, Ivor J. A. Image and Video Processing Computer Vision and Pattern Recognition Medical Physics Introducing accelerated reconstruction algorithms into clinical settings requires measures of uncertainty quantification that accurately assess the relevant uncertainty introduced by the reconstruction algorithm. Many currently deployed approaches quantifying uncertainty by focusing on measuring the variability in voxelwise intensity variation. Although these provide interpretable maps, they lack a structural interpretation and do not show a clear relationship to how the data will be analysed subsequently. In this work we show that voxel level uncertainty does not provide insight into morphological uncertainty. To do so, we use segmentation as a clinically-relevant downstream task and deploy ensembles of reconstruction modes to measure uncertainty in the reconstructions. We show that variability and bias in the morphological structures are present and within-ensemble variability cannot be predicted well with uncertainty measured only by voxel intensity variations. |
| title | Evaluating structural uncertainty in accelerated MRI: are voxelwise measures useful surrogates? |
| topic | Image and Video Processing Computer Vision and Pattern Recognition Medical Physics |
| url | https://arxiv.org/abs/2503.10527 |