{
  "schemaVersion": 4,
  "meta": {
    "name": "Example Vitra",
    "shortDescription": "Ported from CellProfiler ExampleVitra pipeline (nucleus/cytoplasm protein translocation)",
    "description": "Nucleus/cytoplasm protein translocation assay (BBBC014), ported from CellProfiler's ExampleVitra.cppipe. Input: one 4-channel TIFF per well in images/ (Fiji merge): ch0 = DNA (\"Channel 2-*\"), ch1 = protein (\"Channel 1-*\"), ch2 = 1/VitraChannel2ILLUM, ch3 = 1/VitraChannel1ILLUM. CP divides by precomputed illumination functions (.npy, 1.0-2.0 across the field) which evanalyzer cannot load, so the inverse functions are stored as 8-bit extra channels (round(255/f), <0.4 % error) and applied with Image Math MULTIPLY - same correction as CP, not re-estimated.\nNuclei: LI (= CP Minimum Cross-Entropy) threshold computed on the corrected, unsmoothed image (Image Cache + value source) and applied to a sigma-1 Gaussian blur (CP threshold smoothing 1.3488), fill holes, intensity-seeded watershed with CP's automatic values for 5-30 px diameter (maxima suppression 3.33 px, total smoothing sigma 1.43 = 1.0 + 1.02 in quadrature), area 19.6-706.9 px (diameter range), border objects discarded. Threshold mask agrees with CP on 99.7 % of pixels.\nCells (CP Distance-B, 8 px): protein foreground = LI threshold of corrected protein; cell region = (nuclei dilated 8 px AND protein foreground) OR nuclei; Voronoi from the nuclei inside that region. Cytoplasm = cells minus nuclei eroded by 1 px (CP 'shrink smaller object').\nResult vs CP: about 22 % fewer nuclei (577/619 vs 744/782). Evanalyzer's watershed (seeds from intensity, flood on the distance map with 1 px lines) leaves 13-15 dense clumps per image unsplit, which then fail the 30 px diameter limit; lower seed tolerances raise the count but cut single nuclei into fragments. Matched nuclei have about the same area (median eva/CP 0.94-0.95). Cells/cytoplasm of isolated nuclei match CP; in crowded areas they are larger because the missing clump nuclei leave room for their neighbours. The CalculateMath ratios (nucleus/cell and cytoplasm/cell mean protein, computed after export) match closely: median 1.16 vs 1.15 and 1.01 vs 1.03 (nucleus/cell), 0.83 vs 0.80 and 1.00 vs 1.01 (cytoplasm/cell). Evanalyzer measures intensities on raw channels; corrected means were approximated as mean(ch1) x mean(ch3).",
    "authors": [],
    "creationTime": "2026-10-21T00:00:00Z",
    "category": "Intensity",
    "tags": [
      "translocation",
      "nucleus",
      "cytoplasm",
      "cellprofiler"
    ],
    "appVersion": "0.1.0"
  },
  "classification": {
    "classes": [
      {
        "id": 0,
        "color": "#97978f",
        "name": "Background",
        "notes": ""
      },
      {
        "id": 1,
        "color": "#3366ff",
        "name": "nuclei",
        "notes": "Nuclei (IdentifyPrimaryObjects on CorrDNA)"
      },
      {
        "id": 2,
        "color": "#999933",
        "name": "protein@foreground",
        "notes": "Thresholded CorrProtein (IdentifySecondaryObjects' own threshold)"
      },
      {
        "id": 3,
        "color": "#666666",
        "name": "nuclei@expanded",
        "notes": "Nuclei dilated by 8 px (Distance-B reach), helper"
      },
      {
        "id": 4,
        "color": "#888888",
        "name": "cells@reach",
        "notes": "nuclei@expanded AND protein@foreground, helper"
      },
      {
        "id": 5,
        "color": "#aaaaaa",
        "name": "cells@mask",
        "notes": "nuclei OR cells@reach: pixels a cell may occupy, helper"
      },
      {
        "id": 6,
        "color": "#33cc66",
        "name": "cells",
        "notes": "Cells (IdentifySecondaryObjects Distance-B, 8 px)"
      },
      {
        "id": 7,
        "color": "#555599",
        "name": "nuclei@shrunk",
        "notes": "Nuclei eroded by 1 px (IdentifyTertiaryObjects' shrink), helper"
      },
      {
        "id": 8,
        "color": "#ff9933",
        "name": "cytoplasm",
        "notes": "Cytoplasm = cells minus shrunken nuclei (IdentifyTertiaryObjects)"
      }
    ]
  },
  "plate": {
    "groupingMode": "AUTO",
    "groupingRegex": "",
    "plateSize": "AUTO",
    "wellLayout": "AUTO",
    "wellImageOrder": [
      1,
      2,
      3,
      4,
      5,
      6,
      7,
      8,
      9,
      10,
      11,
      12,
      13,
      14,
      15,
      16
    ]
  },
  "pipelines": [
    {
      "id": 1,
      "name": "nuclei",
      "description": "IdentifyPrimaryObjects Nuclei on CorrDNA",
      "imageSource": {
        "channel": 0
      },
      "enabled": true,
      "steps": [
        {
          "id": 1,
          "enabled": true,
          "command": {
            "type": "IMAGE_MATH",
            "operand": "MULTIPLY",
            "secondImageAddress": {
              "channel": 2
            },
            "swapOperands": false
          }
        },
        {
          "id": 2,
          "enabled": true,
          "command": {
            "type": "IMAGE_CACHE",
            "mode": "STORE",
            "address": {
              "memory": {
                "pipelineContext": 1
              }
            }
          }
        },
        {
          "id": 3,
          "enabled": true,
          "command": {
            "type": "GAUSSIAN_BLUR",
            "kernelSize": 7,
            "sigma": 1.0
          }
        },
        {
          "id": 4,
          "enabled": true,
          "command": {
            "type": "THRESHOLD",
            "thresholds": [
              {
                "method": {
                  "type": "LI"
                },
                "minThreshold": 0.0,
                "maxThreshold": 65535.0,
                "unit": "BIT",
                "segmentationClass": 1,
                "valueSource": {
                  "MEMORY": {
                    "pipelineContext": 1
                  }
                }
              }
            ]
          }
        },
        {
          "id": 5,
          "enabled": true,
          "command": {
            "type": "FILL_HOLES"
          }
        },
        {
          "id": 6,
          "enabled": true,
          "command": {
            "type": "CONNECTED_COMPONENTS",
            "minSize": 1
          }
        },
        {
          "id": 7,
          "enabled": true,
          "command": {
            "type": "WATERSHED",
            "maximumFinderTolerance": 3.33,
            "smoothingSigma": 1.02,
            "minObjectSize": 0,
            "seedSource": "INTENSITY"
          }
        },
        {
          "id": 8,
          "enabled": true,
          "command": {
            "type": "FILL_OBJECT_HOLES"
          }
        },
        {
          "id": 9,
          "enabled": true,
          "command": {
            "type": "EXTRACT_OBJECTS",
            "maxObjectsBeforeFail": 100000,
            "classMapping": [
              {
                "segmentationClass": 1,
                "objectClass": {
                  "GLOBAL": 1
                }
              }
            ]
          }
        },
        {
          "id": 10,
          "enabled": true,
          "command": {
            "type": "CLASSIFY_OBJECTS",
            "originSegmentation": [],
            "inputClasses": [
              {
                "GLOBAL": 1
              }
            ],
            "matchHandling": "REMOVE_ALL_CLASSES_IF_NOT_MATCH",
            "outputClass": "UNSET",
            "overlappingWith": "UNSET",
            "minIntersectionArea": 0.0,
            "sizeUnit": "PIXELS",
            "minArea": 19.6,
            "maxArea": 706.9,
            "minCircularity": 0.0,
            "maxCircularity": 1.0,
            "minSolidity": 0.0,
            "maxSolidity": 1.0,
            "minAspectRatio": 0.0,
            "maxAspectRatio": 2147483600.0,
            "minEccentricity": 0.0,
            "maxEccentricity": 1.0,
            "minFeret": 0.0,
            "maxFeret": 2147483600.0,
            "allowEdgeTouching": false,
            "intensityFilters": []
          }
        }
      ]
    },
    {
      "id": 2,
      "name": "protein foreground",
      "description": "Threshold of CorrProtein used by IdentifySecondaryObjects",
      "imageSource": {
        "channel": 1
      },
      "enabled": true,
      "steps": [
        {
          "id": 1,
          "enabled": true,
          "command": {
            "type": "IMAGE_MATH",
            "operand": "MULTIPLY",
            "secondImageAddress": {
              "channel": 3
            },
            "swapOperands": false
          }
        },
        {
          "id": 2,
          "enabled": true,
          "command": {
            "type": "THRESHOLD",
            "thresholds": [
              {
                "method": {
                  "type": "LI"
                },
                "minThreshold": 0.0,
                "maxThreshold": 65535.0,
                "unit": "BIT",
                "segmentationClass": 2,
                "valueSource": "ACTUAL_IMAGE"
              }
            ]
          }
        },
        {
          "id": 3,
          "enabled": true,
          "command": {
            "type": "CONNECTED_COMPONENTS",
            "minSize": 1
          }
        },
        {
          "id": 4,
          "enabled": true,
          "command": {
            "type": "EXTRACT_OBJECTS",
            "maxObjectsBeforeFail": 100000,
            "classMapping": [
              {
                "segmentationClass": 2,
                "objectClass": {
                  "GLOBAL": 2
                }
              }
            ]
          }
        }
      ]
    },
    {
      "id": 3,
      "name": "cells and cytoplasm",
      "description": "IdentifySecondaryObjects (Distance-B) + IdentifyTertiaryObjects",
      "imageSource": "SCRATCHPAD",
      "enabled": true,
      "steps": [
        {
          "id": 1,
          "enabled": true,
          "command": {
            "type": "TRANSFORM_OBJECTS",
            "function": {
              "type": "EXPAND",
              "margin": 8.0,
              "unit": "PIXELS"
            },
            "inputClass": {
              "GLOBAL": 1
            },
            "outputClass": {
              "GLOBAL": 3
            }
          }
        },
        {
          "id": 2,
          "enabled": true,
          "command": {
            "type": "OBJECT_MATH",
            "operation": "AND",
            "inputClass": {
              "GLOBAL": 3
            },
            "otherClass": {
              "GLOBAL": 2
            },
            "otherFilterClasses": [],
            "sizeUnit": "PIXELS",
            "minOverlapArea": 1.0,
            "outputClass": {
              "GLOBAL": 4
            },
            "keepUnmatched": false
          }
        },
        {
          "id": 3,
          "enabled": true,
          "command": {
            "type": "OBJECT_MATH",
            "operation": "OR",
            "inputClass": {
              "GLOBAL": 1
            },
            "otherClass": {
              "GLOBAL": 4
            },
            "otherFilterClasses": [],
            "sizeUnit": "PIXELS",
            "minOverlapArea": 1.0,
            "outputClass": {
              "GLOBAL": 5
            },
            "keepUnmatched": true
          }
        },
        {
          "id": 4,
          "enabled": true,
          "command": {
            "type": "VORONOI",
            "centers": {
              "GLOBAL": 1
            },
            "centerFilterClasses": [],
            "mask": {
              "GLOBAL": 5
            },
            "maskFilterClasses": [],
            "outputClass": {
              "GLOBAL": 6
            },
            "unit": "PIXELS",
            "maxRadius": 0.0,
            "excludeAreasAtTheEdges": false,
            "excludeAreasWithNoCenter": false
          }
        },
        {
          "id": 5,
          "enabled": true,
          "command": {
            "type": "TRANSFORM_OBJECTS",
            "function": {
              "type": "SHRINK",
              "margin": 1.0,
              "unit": "PIXELS"
            },
            "inputClass": {
              "GLOBAL": 1
            },
            "outputClass": {
              "GLOBAL": 7
            }
          }
        },
        {
          "id": 6,
          "enabled": true,
          "command": {
            "type": "OBJECT_MATH",
            "operation": "SUBTRACT",
            "inputClass": {
              "GLOBAL": 6
            },
            "otherClass": {
              "GLOBAL": 7
            },
            "otherFilterClasses": [],
            "sizeUnit": "PIXELS",
            "minOverlapArea": 1.0,
            "outputClass": {
              "GLOBAL": 8
            },
            "keepUnmatched": true
          }
        }
      ]
    }
  ],
  "modules": []
}