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extract_collagen_fibers

Extract collagen fibers from a H&E image.

Parameters:

Name Type Description Default
img ndarray

The input image. Shape (H, W, 3).

 required
label ndarray

The nuclei mask. Shape (H, W). This is used to mask out the nuclei when extracting collagen fibers. If None, the entire image is used.

 None
sigma float

The sigma parameter for the Canny edge detector.

 2.5
rm_bg bool

Whether to remove the background component from the edges.

 False

Returns:

Type Description
ndarray

np.ndarray: The collagen fibers mask. Shape (H, W).

Examples:

>>> from histolytics.data import hgsc_stroma_he
>>> from histolytics.stroma_feats.collagen import extract_collagen_fibers
>>> from skimage.measure import label
>>> from skimage.color import label2rgb
>>> import matplotlib.pyplot as plt
>>>
>>> im = hgsc_stroma_he()
>>> collagen = extract_collagen_fibers(im, label=None)
>>>
>>> fig, ax = plt.subplots(1, 2, figsize=(8, 4))
>>> ax[0].imshow(label2rgb(label(collagen), bg_label=0))
>>> ax[0].set_axis_off()
>>> ax[1].imshow(im)
>>> ax[1].set_axis_off()
>>> fig.tight_layout()

out

Source code in src/histolytics/stroma_feats/collagen.py 
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def extract_collagen_fibers(
    img: np.ndarray,
    label: np.ndarray = None,
    sigma: float = 2.5,
    rm_bg: bool = False,
) -> np.ndarray:
    """Extract collagen fibers from a H&E image.

    Parameters:
        img (np.ndarray):
            The input image. Shape (H, W, 3).
        label (np.ndarray):
            The nuclei mask. Shape (H, W). This is used to mask out the nuclei when
            extracting collagen fibers. If None, the entire image is used.
        sigma (float):
            The sigma parameter for the Canny edge detector.
        rm_bg (bool):
            Whether to remove the background component from the edges.

    Returns:
        np.ndarray: The collagen fibers mask. Shape (H, W).

    Examples:
        >>> from histolytics.data import hgsc_stroma_he
        >>> from histolytics.stroma_feats.collagen import extract_collagen_fibers
        >>> from skimage.measure import label
        >>> from skimage.color import label2rgb
        >>> import matplotlib.pyplot as plt
        >>>
        >>> im = hgsc_stroma_he()
        >>> collagen = extract_collagen_fibers(im, label=None)
        >>>
        >>> fig, ax = plt.subplots(1, 2, figsize=(8, 4))
        >>> ax[0].imshow(label2rgb(label(collagen), bg_label=0))
        >>> ax[0].set_axis_off()
        >>> ax[1].imshow(im)
        >>> ax[1].set_axis_off()
        >>> fig.tight_layout()
    ![out](../../img/collagen_fiber.png)
    """
    if label is not None:
        bg_mask, dark_mask = tissue_components(img, dilation(label, square(5)))

    edges = canny(rgb2gray(img), sigma=sigma, mode="nearest")

    if label is not None:
        edges[dark_mask] = 0
        if rm_bg:
            edges[bg_mask] = 0

    edges = rm_closed_edges(edges)
    edges = remove_small_objects(edges, min_size=35, connectivity=2)

    return edges