Past Work | Relationship to our approach |
---|---|
Co-localization detection | Co-localization detection |
• Spatial image cross-correlation spectroscopy (ICCS) [1,2,3,4] - Pearson, Spearman’s rank. | • ICCS is not applicable since it does not capture spatial information. |
• Replaced manual segmentation with automated object-based analysis. | |
• Object-based analysis [35] with manual segmentation. | |
Foreground modeling | Foreground modeling |
• Statistical: scatterplot of two channel intensities [4] with a single model. | • Statistical: used scatterplot with optimization over multiple statistical models. |
• Geometrical: fiber segmentation based on many software packages including IvanTK, NeuronJ, Simple Neurite Tracer, Vaa3D, and Vascular Modelling Toolkit (VMTK). | • Geometrical: could not use existing software designed for vascular or brain structures (not fiber scaffolds), and some software worked only in 2D and required manual identification of end points. |
Validation of 3D Segmentation | Validation of 3D Segmentation |
• Manual reference is hard to create for 3D objects. | |
• Orthogonal measurements using μCT, SEM and CLSM [42], and mSPIM [43]. | • Used orthogonal measurements of a single fiber imaged via multi-view 2D SEM and 3D CLSM. |
Visual verification of 3D contacts at large scale | Visual verification of 3D contacts at large scale |
• Not aware of any previous work. | • We designed a web system with three orthogonal max projections and 6 animated movies per contact. |