Limitations of clDice for Evaluating Pancreatic Duct Segmentation in CT

Background/Objectives: Centerline Dice (clDice) emphasizes skeleton overlap, but a high score does not establish connectivity. This empirical study, which proposes no new metric, measured how often high-scoring pancreatic-duct segmentations on computed tomography (CT) differ from their references in connected-component count, and what changes that frequency. Methods: Dice, clDice and component counts were compared for 235 held-out PANORAMA CT predictions of a public model. The references were algorithm-generated, so a difference shows disagreement, not anatomical correctness. Thresholds, small-component cleanup and skeleton-based counting were varied. Further tests used a second model, known cuts, synthetic tubes and retinal labels. Synthetic-tube radii illustrate the mechanism, not clinical thresholds. Results: Among 81 predictions with both scores above 0.85, 51 (63.0%; 95% CI 52–73%) differed in component count; a second model gave 32 of 55 (58.2%). Among 86 predictions with Dice above 0.85, cleanup alone moved discordant cases between 25 and 60, and skeleton-based counting reclassified seven cases. After one known cut, 194 of 199 references kept both scores above 0.85 despite the break. Conclusions: High clDice does not ensure matching connectivity. Studies should report a direct connectivity measure alongside clDice and state their cleanup and skeletonization conventions, because these conventions alone changed the reported frequency.

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Publication Details

Journal
Tomography
Published
2026-10-27
DOI
https://doi.org/10.3390/tomography12110155
Primary Topic
Medical Image Segmentation Techniques
Type
article
Field-Weighted Citation Impact
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article

Limitations of clDice for Evaluating Pancreatic Duct Segmentation in CT

André Mastmeyer, Negar Chabi, Souraj Adhikary
2 links
Tomography
Medical Image Segmentation Techniques
article

Limitations of clDice for Evaluating Pancreatic Duct Segmentation in CT

André Mastmeyer, Negar Chabi, Souraj Adhikary
article en

Abstract

Background/Objectives: Centerline Dice (clDice) emphasizes skeleton overlap, but a high score does not establish connectivity. This empirical study, which proposes no new metric, measured how often high-scoring pancreatic-duct segmentations on computed tomography (CT) differ from their references in connected-component count, and what changes that frequency. Methods: Dice, clDice and component counts were compared for 235 held-out PANORAMA CT predictions of a public model. The references were algorithm-generated, so a difference shows disagreement, not anatomical correctness. Thresholds, small-component cleanup and skeleton-based counting were varied. Further tests used a second model, known cuts, synthetic tubes and retinal labels. Synthetic-tube radii illustrate the mechanism, not clinical thresholds. Results: Among 81 predictions with both scores above 0.85, 51 (63.0%; 95% CI 52–73%) differed in component count; a second model gave 32 of 55 (58.2%). Among 86 predictions with Dice above 0.85, cleanup alone moved discordant cases between 25 and 60, and skeleton-based counting reclassified seven cases. After one known cut, 194 of 199 references kept both scores above 0.85 despite the break. Conclusions: High clDice does not ensure matching connectivity. Studies should report a direct connectivity measure alongside clDice and state their cleanup and skeletonization conventions, because these conventions alone changed the reported frequency.

TomographyVol. 12(11)
Jade University of Applied Sciences (DE)
Deutsche Forschungsgemeinschaft
Good health and well-being
Openalex Percentile: Top 17%
Medical Image Segmentation Techniques
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