Data from: A semi-automated pipeline for morphological analysis of myonuclei along single muscle fibers

Manual quantitation of skeletal muscle myonuclear number, spatial
orientation, and morphology is time consuming and subject to error and
bias. To overcome these limitations, we developed and validated a
semi-automated, quantitative, and reproducible image analysis pipeline.
The workflow combines FIJI-based preprocessing with custom Python scripts
to process immunohistological images of individual muscle fibers, enabling
high resolution and scalable quantification of nuclei. Analyses
incorporate morphometric parameters including nuclear position, shape, and
three dimensional orientation, as well as centroid to skeleton distance
and nearest neighbor relationships to capture spatial patterns of
myonuclear organization along the fiber. Outputs include per fiber and
biopsy level summaries integrated with Imaris metrics. This semi-automated
approach provides a robust and efficient platform for high throughput
analysis of myonuclear number and structural features across large single
fiber datasets.