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dominant_stains

Estimates dominant stain vectors for a given image.

Parameters:

Name Type Description Default
img RGBImage

Tissue stained with two stains.

 required
i0 int

Transmitted light intensity (i.e., what is the intensity of light that passed through no tissue).

 240
alpha int

Percentile offset for robust stain estimation.

 1
beta float

Threshold for removing transparent pixels in OD-space.

 0.15
Note

Default values for i0, alpha, and beta parameters are inspired by the reference implementation.

Returns:

Type Description
DominantStains

Dictionary with two dominant stains.
Note

The returned dictionary contains the following values:

Key Description
stain1 First dominant stain vector.
stain2 Second dominant stain vector.

Examples: 

from skimage.data import immunohistochemistry

from rationai.qc.staining import dominant_stains


img = immunohistochemistry()
result = dominant_stains(img=img)

stain1, stain2 = result["stain1"], result["stain2"]

# Values should be somewhat close to Hematoxylin and DAB stain vectors.
print(stain1, stain2)

Source code in rationai/qc/staining/dominant_stains.py 
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def dominant_stains(
    img: RGBImage, i0: int = 240, alpha: int = 1, beta: float = 0.15
) -> DominantStains:
    """Estimates dominant stain vectors for a given image.

    Args:
        img: Tissue stained with two stains.
        i0: Transmitted light intensity (i.e., what is the intensity of light
            that passed through no tissue).
        alpha: Percentile offset for robust stain estimation.
        beta: Threshold for removing transparent pixels in OD-space.

    Note:
        Default values for `i0`, `alpha`, and `beta` parameters are inspired
        by the <a href="https://github.com/schaugf/HEnorm_python">reference implementation</a>.

    Returns:
        Dictionary with two dominant stains.

    Note:
        The returned dictionary contains the following values:

        | Key       | Description                     |
        |-----------|---------------------------------|
        | `stain1`  | First dominant stain vector.    |
        | `stain2`  | Second dominant stain vector.   |

    Examples:
    ```python
    from skimage.data import immunohistochemistry

    from rationai.qc.staining import dominant_stains


    img = immunohistochemistry()
    result = dominant_stains(img=img)

    stain1, stain2 = result["stain1"], result["stain2"]

    # Values should be somewhat close to Hematoxylin and DAB stain vectors.
    print(stain1, stain2)
    ```
    """
    stain1, stain2 = estimate_stain_vectors(img=img, i0=i0, alpha=alpha, beta=beta)

    result: DominantStains = {
        "stain1": stain1,
        "stain2": stain2,
    }

    return result