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).
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 for running stages in isolated environments.