# pyCyto Analysis Pipeline

pyCyto processes time-lapse microscopy data through six ordered stages, each defined declaratively in a YAML configuration file (see the config template in your release package).

```{mermaid}
graph TD
    A([Raw Microscopy Images]) --> AA[Spatial Tiling]
    AA --> B([File I/O: Load Channels])

    B --> C[Preprocessing]
    C --> D[Register and Denoise]
    C --> E[Channel Merge]
    C --> F[Intensity Normalization]
    C --> G[Gamma Correction]
    D --> H[Segmentation]
    E --> H
    F --> H
    G --> H

    H --> I[Cellpose]
    H --> J[StarDist]
    I --> K[Tabulation]
    J --> K

    K --> L[Label to Sparse Features]
    L --> M[Tracking]

    M --> N[TrackMate sparse]
    M --> O[trackpy sparse]
    M --> P[Ultrack dense]
    N --> Q[Analysis]
    O --> Q
    P --> Q

    Q --> R[Contact Tracing]
    Q --> S[Kinematics]
    Q --> T[Cell Networks]
    R --> U([Results: Tables, Plots, Networks])
    S --> U
    T --> U

    classDef stageIO      fill:#1e293b,color:#f1f5f9,stroke:#475569
    classDef stagePre     fill:#0d7377,color:#fff,stroke:#0a5c60
    classDef stageSeg     fill:#7c3aed,color:#fff,stroke:#6d28d9
    classDef stageTab     fill:#0369a1,color:#fff,stroke:#075985
    classDef stageTrack   fill:#0369a1,color:#fff,stroke:#075985
    classDef stageAna     fill:#b45309,color:#fff,stroke:#92400e
    classDef stageOut     fill:#166534,color:#fff,stroke:#14532d
    classDef stageOpt     fill:#6b7280,color:#fff,stroke:#4b5563

    class A,B stageIO
    class C,D,E,F stagePre
    class G stageOpt
    class H,I,J stageSeg
    class K,L stageTab
    class M,N,O stageTrack
    class P stageOpt
    class Q,R,S,T stageAna
    class U stageOut
    class AA stageOpt
```

See the config template in your release package for the YAML fields behind each stage, and [Containerized Execution](containerized_execution.md) for running stages in isolated environments.