Use euclidian flow do decide about pixel assignment

[Czaki]

Instead of uuse of grayscale dilate, use binary dilate to decide about area and then use euclidean flow to assign pixel membership.

Summary by CodeRabbit

• Improvements
  • Enhanced the dilation process in segmentation to use a more advanced sprawl-based approach, improving how regions are expanded and potentially offering more accurate results in complex images.

[coderabbitai]

Walkthrough

The dilation logic within the ThresholdFlowAlgorithmWithDilation.calculation_run method was replaced. Instead of a basic morphological dilation, the method now uses a sprawl-based approach involving conversion to a binary image, computation of neighborhoods and distances, and the use of a compiled sprawl function to generate the final dilated ROI.

Changes

File(s)	Change Summary
src/PartSeg_smfish/segmentation.py	Updated dilation logic in ThresholdFlowAlgorithmWithDilation.calculation_run to use sprawl-based algorithm. Imported new functions for binary conversion, neighborhood, distance calculation, and sprawl.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant ThresholdFlowAlgorithmWithDilation
    participant PartSegCore.image_operations
    participant PartSegCore.segmentation.watershed
    participant PartSegCore_compiled_backend.sprawl_utils.find_split

    User->>ThresholdFlowAlgorithmWithDilation: calculation_run()
    ThresholdFlowAlgorithmWithDilation->>PartSegCore.image_operations: to_binary_image(ROI)
    ThresholdFlowAlgorithmWithDilation->>PartSegCore.segmentation.watershed: get_neigh(), calculate_distances_array()
    ThresholdFlowAlgorithmWithDilation->>PartSegCore_compiled_backend.sprawl_utils.find_split: euclidean_sprawl(dilated_mask, ROI, ...)
    ThresholdFlowAlgorithmWithDilation-->>User: ROIExtractionResult (with new dilated ROI)

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Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~15 minutes

Poem

A sprawl of code, a gentle spread,
Where labels grew, new logic led.
No longer just a simple swell—
Distances guide where pixels dwell.
With binary masks and neighbors near,
The rabbit hops, the path is clear!
🐇✨

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📥 Commits

Reviewing files that changed from the base of the PR and between 9f9dee4 and edbabc2.

📒 Files selected for processing (1)

• src/PartSeg_smfish/segmentation.py (3 hunks)

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• GitHub Check: ubuntu-latest py3.10
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• GitHub Check: macos-latest py3.12
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🔇 Additional comments (3)

src/PartSeg_smfish/segmentation.py (3)

17-17: Import statements are well-organized and appropriate.

The added imports provide the necessary functionality for the Euclidean flow-based pixel assignment approach.

Also applies to: 40-47

---

737-749: Excellent improvement to the dilation algorithm!

The replacement of simple morphological dilation with Euclidean flow-based pixel assignment is a significant enhancement. This approach will:

• Respect component boundaries more accurately
• Assign pixels based on actual distances considering image spacing
• Provide more predictable results for touching or nearby components

---

741-741: Confirm the hardcoded boolean in get_neigh(True)
Hard-coding True here forces one connectivity mode (e.g., full 3D adjacency). Please review the signature and docstring of PartSegCore.segmentation.watershed.get_neigh in your dependency to ensure that True is the intended setting for 3D connectivity. Adjust this argument or make it configurable if another mode is required.

• Location: src/PartSeg_smfish/segmentation.py:741
• Context:

neigh, dist = calculate_distances_array(
    self.image.spacing, get_neigh(True)
)

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