Diameter Analysis¶
Diameter analysis estimates vessel diameter from line scan kymographs.
The analysis operates on intensity profiles derived from a selected ROI and produces diameter summaries, per-row or per-window results, and quality-control values.
Input data¶
Diameter analysis expects image data organized as a line scan kymograph. The ROI should cover the spatial region used to estimate vessel diameter.
Detection parameters¶
Detection parameters define the scientific behavior of the analysis. Diameter analysis parameters control profile aggregation, polarity, thresholding, gradient-based edge detection, motion gating, and post-filtering.
Diameter Detection Parameters¶
| name | display_name | type | default | choices | unit | editable | visible | methods | description |
|---|---|---|---|---|---|---|---|---|---|
| window_rows_odd | Window Rows (Odd) | int | 5 | True | True | ('threshold_width', 'gradient_edges') | Odd number of time rows aggregated into each spatial profile. | ||
| stride | Stride | int | 1 | True | True | ('threshold_width', 'gradient_edges') | Center-row increment between successive measurements. | ||
| binning_method | Binning Method | enum | mean | ('mean', 'median') | True | True | ('threshold_width', 'gradient_edges') | Window reducer across rows before edge detection. | |
| polarity | Polarity | enum | bright_on_dark | ('bright_on_dark', 'dark_on_bright') | True | True | ('threshold_width', 'gradient_edges') | Intensity polarity; dark_on_bright inverts the profile. | |
| diameter_method | Detection Method | enum | threshold_width | ('threshold_width', 'gradient_edges') | True | True | Core detector implementation. | ||
| post_filter_kernel_size | Post-Filter Kernel Size | int | 3 | True | True | Odd median kernel applied to diameter after detection. Post-detection smoothing; re-run analysis to apply changes. | |||
| threshold_mode | Threshold Mode | enum | half_max | ('half_max', 'absolute') | True | True | ('threshold_width',) | Threshold rule for threshold_width. | |
| threshold_value | Threshold Value | float | 0.0 | True | True | ('threshold_width',) | Absolute threshold when threshold_mode='absolute'. | ||
| gradient_sigma | Gradient Sigma | float | 1.5 | True | True | ('gradient_edges',) | Gaussian smoothing sigma for gradient edge finding. | ||
| gradient_kernel | Gradient Kernel | enum | central_diff | ('central_diff',) | True | True | ('gradient_edges',) | Derivative kernel for gradient_edges. | |
| gradient_min_edge_strength | Min Edge Strength | float | 0.02 | True | True | ('gradient_edges',) | Minimum derivative magnitude for a confident edge. | ||
| enable_motion_gating | Enable Motion Gating | bool | True | True | True | ('gradient_edges',) | Apply frame-to-frame motion constraints for gradient_edges. | ||
| max_edge_shift_um | Max Edge Shift (um) | float | 2.0 | True | True | ('gradient_edges',) | Maximum allowed per-frame left/right edge shift. | ||
| max_diameter_change_um | Max Diameter Change (um) | float | 2.0 | True | True | ('gradient_edges',) | Maximum allowed per-frame diameter jump. | ||
| max_center_shift_um | Max Center Shift (um) | float | 2.0 | True | True | ('gradient_edges',) | Maximum allowed per-frame center shift. |
Results¶
Diameter analysis stores summary values in the AcqImage JSON sidecar and writes tabular output to a CSV file.
For a source file named my_file.tif, diameter analysis saves:
my_file.tif.json
my_file.tif.diameter.csv
The JSON sidecar includes the detection parameters and summary values for each analyzed ROI. Typical summary values include:
diameter_um_meandiameter_um_mediandiameter_um_cvnum_rowsqc_score_mean- quality-control violation counts
The CSV file stores tabular diameter results.
Programmatic use¶
Diameter analysis can be run from the GUI or from Python code using the same acqstore backend.
See the Diameter Analysis API.