Journal: Bone Reports
Article Title: A novel workflow for 3D imaging and spatial analysis of nerves in bone ☆
doi: 10.1016/j.bonr.2025.101881
Figure Lengend Snippet: Combined Ilastik®, ImageJ, and Imaris® processing pipeline. A) Individual z-slices were selected from the 3D LSM image that represented the inter-condition, inter-replicate, and intra-sample variability. The Ilastik® classifier was trained to select “nerve” and “not nerve” or background data. Post-training, Ilastik® segmentation was applied to all the z-slices in each 3D image. Samples were then processed in ImageJ to generate binary nerve masks. Binary nerve masks were imported back into Imaris® for 3D segmentation, and re-masking for statistical analyses. B) Comparison of Imaris® intensity-based segmentation and 3D reconstruction with Ilastik® machine learning segmentation and Imaris® 3D reconstruction. Scale bar = 100 μm. C) Comparison of Ilastik® machine learning segmentation with one, two, or four training slices. One and two training slices were intra-sample slices, while four slices combined two sets of intra-sample slices from two independent replicates. Scale bar = 100 μm.
Article Snippet: Comparing the Ilastik® pipeline with Imaris® intensity-based segmentation, we demonstrated improved segmentation of nerve-like structures, with reduced segmentation of non-nerve background ( B).
Techniques: Comparison