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🔬 CT Phenotyping System
Non-destructive X-ray CT phenotyping using a clinical dual-source CT scanner (SOMATOM Definition AS+, Siemens Healthineers). The system covers the complete pipeline from image acquisition to biological interpretation.
Technical Specifications
| Parameter | Value |
|---|---|
| Scanner | SOMATOM Definition AS+ (dual-source) |
| Tube voltage | 120 kV |
| Tube current | 200 mAs |
| Slice thickness | 0.6 mm |
| Matrix | 512 × 512 |
| Reconstruction kernel | B30f (medium-smooth) |
| Total slices | 7,686 DICOM |
| Varieties × Stages | 5 varieties × 5 developmental stages |
Pipeline
- Automated equatorial slice selection — maximizes cross-sectional area
- Tissue segmentation — DeepLabV3+ with improved backbone (Liu et al., 2023, Front. Plant Sci.)
- Multi-compartment quantification — fiber, shell, endosperm, water cavity (Lin et al., 2023, PLOS ONE)
- 3D volume rendering — non-invasive volumetric analysis (Zhang et al., 2023, Plant Methods)
- 78 phenotypic parameters — including CT values, tissue thicknesses, volumes, and morphological indices
Key Publications
- Zhang Y et al. (2023) Developing non-invasive 3D quantificational imaging for intelligent coconut analysis system with X-ray. Plant Methods 19, 24.
- Liu Q et al. (2023) An improved DeepLab V3+ network based coconut CT image segmentation method. Frontiers in Plant Science 14, 1139666.
- Lin S et al. (2023) Visualization and quantification of coconut using advanced computed tomography postprocessing technology. PLOS ONE 18(2), e0282182.
- Lin S et al. (2025) The observation of internal structure changes and survival prediction modeling of mature coconut during germination based on computed tomography imaging. Industrial Crops & Products 233, 121396.