Create an Annotation Project

Gesund.ai allows users to create annotation projects for various data types including CT, MRI, PET, and whole slide microscopy. This guide walks through the general steps to configure and launch a new project, including project setup, team assignment, and labeling configuration.

In the video below, we demonstrate these steps using a 3D CT dataset as an example. However, the same workflow applies to 2D datasets and microscopy projects as well.

1. What This Tutorial Covers

1. Selecting a dataset from the platform or uploading your own
2. Setting up a new annotation project with viewer settings
3. Assigning team members and samples
4. Creating a labeling configuration using Segmentation with Mask annotations

2. Key Concepts

1. Viewer Mode: Choose 2D, 3D, or WSI viewer depending on dataset type
2. Annotation Type: Mask (pixel-wise), Polygon, or other supported types
3. Problem Type: Segmentation or Classification
4. AI Assistance: Optionally enabled for loading pre-annotations automatically

The steps shown apply to a 3D CT project, but the same structure can be used for microscopy or 2D datasets.

3. Supported Use Cases

1. CT, MRI, PET datasets in DICOM or NIfTI format
2. Whole slide images for pathology and microscopy annotation
3. Lesion, organ, or region segmentation in both 2D and 3D
4. Projects with manual, semi-automatic, or fully AI-assisted workflows

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Note: UI elements may evolve, but the project creation flow remains consistent across different annotation types.