Workflow#
This section gives a broad overview of the steps taken in processing images.
Topotracing : Processing a single .spm file#
Topotracing loads images from .spm files and extracts the specified channel, performing various filtering stages
(Filters() class) before finding grains (Grains() class) and then calculating statistics for each grain
(GrainStats() class). The Gaussian filtered image and labelling of grains is then passed onto DNA Tracing.
%%{init: {'theme': 'base',
}
}%%
graph TD;
subgraph Background Flattening
A1([Load YAML Configuration]) --> A2([Load SPM])
A2 --> A3([Extract channel from SPM])
A3 --> A4([Initial Align])
A4 --> A5([Initial Tilt Removal])
A5 --> A6([Thresholding Otsu])
A6 --> A7([Mask Generation])
A7 --> A8([Masked Align])
A8 --> A9([Masked Tilt Removal])
A9 --> A10([Background Zeroing])
end
subgraph Grain Finding
A10 --> B1([Lower Thresholding])
B1 --> B2([Gaussian Filtering])
B2 --> B3([Tidy Edges])
B3 --> B4([Preliminary Statistics])
B4 --> B5([Size Thresholding])
B5 --> B6([Label Regions])
end
subgraph Grain Statistics
B6 --> C2([Calculate Points])
C2 --> C8([Height & Volume Statistics])
C2 --> C3([Calculate Edges])
C2 --> C4([Calculate Centroid])
C3 --> C5([Calculate Radius Statistics])
C3 --> C6([Convex Hull / Graham Scan])
C6 --> C7([Minimum Bounding Box Statistics])
end
subgraph DNA Tracing
B2 --> D1([More Analysis])
B5 --> D1
end
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style A4 fill:#648FFF,stroke:#000000
style A5 fill:#648FFF,stroke:#000000
style A6 fill:#648FFF,stroke:#000000
style A7 fill:#648FFF,stroke:#000000
style A8 fill:#648FFF,stroke:#000000
style A9 fill:#648FFF,stroke:#000000
style A10 fill:#648FFF,stroke:#000000
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style B2 fill:#DC267F,stroke:#000000
style B3 fill:#DC267F,stroke:#000000
style B4 fill:#DC267F,stroke:#000000
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style B6 fill:#DC267F,stroke:#000000
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style C5 fill:#FE6100,stroke:#000000
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DNA Tracing : Processing a single grain#
%%{init: {'theme': 'base',
}
}%%
graph TD;
subgraph dnaTrace
A1(["get_numpy_arrays() | Load Numpy arrays to dictionary indexed by number"]) --> A2(["skimage.filters.gaussian() | Filter full image"])
A2 -- For each image --> A3(["get_disordered_trace() | extracts mask"])
A3 --> A4(["purge_obvious_crap() | Removes ites if len() < 10 (i.e. small objects) "])
A4 --> A5(["linear_or_circular on unordered traces() | linear or circular molecule"])
A5 --> A6(["get_ordered_traces() | Reorders points in the array?"])
A6 --> A7(["linear_or_circular() on ordered traces"])
A7 --> A8(["get_fitted_traces()"])
A8 --> A9(["get_splined_traces()"])
A9 --> A10(["measure_contour_length()"])
A10 --> A11(["measure_end_to_end_distance()"])
A11 --> A12(["report_basic_stats()"])
end
subgraph "get_disordered_trace()"
A3 --> B1(["ndimage.binary_dilation() | extracts mask"])
B1 --> B2(["scipy.ndimage.gaussian_filter molecule()"])
B2 --> B3(["getSkeleton()"])
B3 --> A4
end
subgraph "getSkeleton()"
B3 --> C1(["Skeletonize | to be replaced by get_skeleton()"])
C1 --> B3
end
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style C1 fill:#FE6100,stroke:#000000