Three-dimensional mitochondrial volume measurements show systematic biases and resolution effects
Representation Bias, Correction Transfer, and Resolution Sensitivity in Three-Dimensional Mitochondrial Morphometry
Artificial Intelligence
Summary
Measuring the size and shape of 3D mitochondria from images can be very precise but still have consistent errors. The authors studied how one measurement method slightly overestimates volume compared to a reference and identified why. They found a way to reduce this error by adjusting how labels are processed, but some errors remain. Also, measuring details at different image resolutions changes some shape estimates, showing that measurement settings can affect results.
What this means in practice
- •For biomedical imaging teams: Improve accuracy of mitochondrial volume measurements by correcting label displacement errors in 3D image processing pipelines.
- •For electron microscopy analysts: Assess how image resolution changes affect mitochondrial shape descriptors for more reliable morphometry comparisons.
Authors
Farouk Ganiyu Adewumi, Timothy Oladunni
Abstract
Quantitative imaging pipelines can produce precise but systematically different measurements of the same object. We present an empirical reliability assessment of three-dimensional mitochondrial morphometry that connects representation bias, a controlled processing intervention, correction transfer, and resolution sensitivity. Using 2,720 development objects from the 3D Mitochondria Shape Library for Optical Microscopy, we find that occupancy-derived volumes exceed reference mesh volumes by 3.665% on average despite an intraclass correlation coefficient of 0.994. Boundary analysis identifies an outward label displacement of 0.00304 normalized units. In a controlled label-pipeline reimplementation, removing the depth offset reduces volume error in all 55 analyzed objects by a mean of 1.57 percentage points, approximately 45% of mean reproduced inflation; the source of the remainder is not isolated. A frozen regression using occupancy-derived features reduces median absolute percentage error from 3.481% to 0.664% in 2,728 previously unused objects from the same resource. However, its calibrated error bound covers only 92.1% overall and 49.2% in a low-occupancy subgroup, demonstrating that accuracy and uncertainty transfer must be evaluated separately. In 550 rat-cortex objects from the MitoEM resource, coarsening in-plane spacing from 8 to 24 nanometers changes median surface area by minus 10.60% and sphericity by plus 11.76%, despite a rank correlation of 0.994. These results provide quantitative checks for distinguishing processing-induced descriptor changes from candidate biological differences, without establishing biological invariance or cross-source correction transfer.