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‎fractal_tasks_core/dev/task_info/apply_registration_to_image.md‎

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### Purpose
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- Applies pre-calculated registration transformations to images in an HCS OME-Zarr dataset, aligning all acquisitions to a specified reference acquisition.
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- Masks regions not included in the registered ROI table and aligns both intensity and label images.
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- **Applies pre-calculated registration** transformations to images in an **HCS** OME-Zarr dataset, aligning all acquisitions to a specified reference acquisition.
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- **Masks regions not included** in the registered ROI table and aligns both intensity and label images.
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- Replaces the non-aligned image with the newly aligned image in the dataset if `overwrite input` is selected.
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- Typically used as the third task in a workflow, following `Calculate Registration (image-based)` and `Find Registration Consensus`.
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‎fractal_tasks_core/dev/task_info/calculate_registration_image_based.md‎

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### Purpose
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- Computes image-based registration transformations for acquisitions in HCS OME-Zarr datasets.
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- **Computes image-based registration** transformations for acquisitions in **HCS** OME-Zarr datasets.
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- Processes images grouped by well, under the assumption that each well contains one image per acquisition.
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- Calculates transformations for specified regions of interest (ROIs) and stores the results in the corresponding ROI table.
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- Calculates transformations for **specified regions of interest (ROIs)** and stores the results in the corresponding ROI table.
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- Typically used as the first task in a workflow, followed by `Find Registration Consensus` and optionally `Apply Registration to Image`.
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### Limitations

‎fractal_tasks_core/dev/task_info/cellpose_segmentation.md‎

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### Purpose
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- Segments images using Cellpose models.
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- Supports both built-in Cellpose models (shipped with Cellpose) and user-trained models.
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- **Segments images using Cellpose models**.
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- Supports both **built-in Cellpose models** (shipped with Cellpose) and **user-trained models**.
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- Accepts dual image input for segmentation.
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- Can process arbitrary regions of interest (ROIs), including whole images, fields of view (FOVs), or masked outputs from prior segmentations, based on corresponding ROI tables.
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- Can process **arbitrary regions of interest (ROIs)**, including whole images, fields of view (FOVs), or masked outputs from prior segmentations, based on corresponding ROI tables.
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- Provides access to all advanced Cellpose parameters.
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- Allows custom rescaling options per channel, particularly useful for sparse images.
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‎fractal_tasks_core/dev/task_info/convert_cellvoyager_multiplex.md‎

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### Purpose
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- Converts multiplexed 2D and 3D images from CellVoyager CV7000/8000 systems into OME-Zarr format, storing each acquisition as a separate OME-Zarr image in the same OME-Zarr plate.
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- Creates OME-Zarr HCS plates, combining all fields of view for each acquisition in a well into a single image.
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- Saves Fractal region-of-interest (ROI) tables for both individual fields of view and the entire well.
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- Converts **multiplexed 2D and 3D images from CellVoyager CV7000/8000** systems into OME-Zarr format, storing each acquisition as a separate OME-Zarr image in the same OME-Zarr plate.
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- Creates **OME-Zarr HCS plates**, combining all fields of view for each acquisition in a well into a single image.
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- Saves Fractal **region-of-interest (ROI) tables** for both individual fields of view and the entire well.
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- Handles overlapping fields of view by adjusting their positions to be non-overlapping, while preserving the original position data as additional columns in the ROI tables.
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### Limitations

‎fractal_tasks_core/dev/task_info/convert_cellvoyager_to_ome_zarr.md‎

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### Purpose
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- Converts 2D and 3D images from CellVoyager CV7000/8000 systems into OME-Zarr format, creating OME-Zarr HCS plates and combining all fields of view in a well into a single image.
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- Saves Fractal region-of-interest (ROI) tables for both individual fields of view and the entire well.
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- Converts **2D and 3D images from CellVoyager CV7000/8000** systems into OME-Zarr format, creating OME-Zarr HCS plates and combining all fields of view in a well into a single image.
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- Saves Fractal **region-of-interest (ROI) tables** for both individual fields of view and the entire well.
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- Handles overlapping fields of view by adjusting their positions to be non-overlapping while retaining the original position data as additional columns in the ROI tables.
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- Supports processing multiple plates in a single task.
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‎fractal_tasks_core/dev/task_info/find_registration_consensus.md‎

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### Purpose
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- Determines the consensus alignment region across all selected acquisitions within each well of an HCS OME-Zarr dataset.
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- Determines the **consensus alignment** region across all selected acquisitions **within each well of an HCS OME-Zarr dataset**.
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- Generates a new ROI table for each image, defining consensus regions that are aligned across all acquisitions.
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- Typically used as the second task in a workflow, following `Calculate Registration (image-based)` and optionally preceding `Apply Registration to Image`.
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‎fractal_tasks_core/dev/task_info/illumination_correction.md‎

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### Purpose
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- Corrects illumination in OME-Zarr images using pre-calculated flatfield profiles.
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- Optionally performs background subtraction.
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- **Corrects illumination** in OME-Zarr images using **pre-calculated flatfield profiles**.
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- Optionally performs **background subtraction**.
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### Limitations
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- Requires pre-calculated flatfield profiles in TIFF format.

‎fractal_tasks_core/dev/task_info/import_ome_zarr.md‎

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### Purpose
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- Imports a single OME-Zarr dataset into the Fractal framework for further processing.
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- Supports importing either a full OME-Zarr HCS plate or an individual OME-Zarr image.
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- Imports a **single OME-Zarr dataset** into the Fractal framework for further processing.
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- Supports importing either a **full OME-Zarr HCS plate** or an **individual OME-Zarr image**.
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- Ensures the OME-Zarr dataset is located in the `zarr_dir` specified by the dataset.
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- Generates the necessary image list metadata required for processing the OME-Zarr with Fractal.
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- Optionally adds new ROI tables to the existing OME-Zarr, enabling compatibility with many other tasks.
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- Generates the necessary **image list metadata** required for processing the OME-Zarr with Fractal.
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- Optionally **adds new ROI tables** to the existing OME-Zarr, enabling compatibility with many other tasks.
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### Limitations
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- Supports only OME-Zarr datasets already present in the `zarr_dir` of the corresponding dataset.

‎fractal_tasks_core/dev/task_info/napari_workflows_wrapper.md‎

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### Purpose
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- Executes a Napari workflow on the regions of interest (ROIs) within a single OME-NGFF image.
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- Executes a **napari workflow** on the regions of interest (ROIs) within a single OME-NGFF image.
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- Processes specified images and labels as inputs to the workflow, producing outputs such as new labels and data tables.
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- Offers flexibility in defining input and output specifications to customize the workflow for specific datasets and analysis needs.
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- Offers **flexibility in defining input and output** specifications to customize the workflow for specific datasets and analysis needs.
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### Limitations
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- Currently supports only Napari workflows that utilize functions from the `napari-segment-blobs-and-things-with-membranes` module. Other Napari-compatible modules are not supported.

‎fractal_tasks_core/dev/task_info/projection.md‎

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### Purpose
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- Performs Z-axis projection of intensity images using a specified projection method.
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- Generates a new OME-Zarr HCS plate to store the projected data.
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- Performs **Z-axis projection of intensity images** using a specified projection method.
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- **Generates a new OME-Zarr HCS plate** to store the projected data.
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### Limitations
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- Supports projections only for OME-Zarr HCS plates; other collections of OME-Zarrs are not yet supported.

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