histomicstk.segmentation.positive_pixel_count¶
- class histomicstk.segmentation.positive_pixel_count.Output(NumberWeakPositive, NumberPositive, NumberStrongPositive, NumberTotalPixels, IntensitySumWeakPositive, IntensitySumPositive, IntensitySumStrongPositive, IntensityAverage, RatioStrongToTotal, IntensityAverageWeakAndPositive, RatioStrongToPixels, RatioWeakToPixels, RatioTotalToPixels)¶
Bases:
tuple
- IntensityAverage¶
Alias for field number 7
- IntensityAverageWeakAndPositive¶
Alias for field number 9
- IntensitySumPositive¶
Alias for field number 5
- IntensitySumStrongPositive¶
Alias for field number 6
- IntensitySumWeakPositive¶
Alias for field number 4
- NumberPositive¶
Alias for field number 1
- NumberStrongPositive¶
Alias for field number 2
- NumberTotalPixels¶
Alias for field number 3
- NumberWeakPositive¶
Alias for field number 0
- RatioStrongToPixels¶
Alias for field number 10
- RatioStrongToTotal¶
Alias for field number 8
- RatioTotalToPixels¶
Alias for field number 12
- RatioWeakToPixels¶
Alias for field number 11
- class histomicstk.segmentation.positive_pixel_count.Parameters(hue_value, hue_width, saturation_minimum, intensity_upper_limit, intensity_weak_threshold, intensity_strong_threshold, intensity_lower_limit)[source]¶
Bases:
Parameters
Parameters(hue_value, hue_width, saturation_minimum, intensity_upper_limit, intensity_weak_threshold, intensity_strong_threshold, intensity_lower_limit)
- hue_value¶
Center of the hue range in HSI space for the positive color, in the range [0, 1]
- hue_width¶
Width of the hue range in HSI space
- saturation_minimum¶
Minimum saturation of positive pixels in HSI space, in the range [0, 1]
- intensity_upper_limit¶
Intensity threshold in HSI space above which a pixel is considered negative, in the range [0, 1]
- intensity_weak_threshold¶
Intensity threshold in HSI space that separates weak-positive pixels (above) from plain positive pixels (below)
- intensity_strong_threshold¶
Intensity threshold in HSI space that separates plain positive pixels (above) from strong positive pixels (below)
- intensity_lower_limit¶
Intensity threshold in HSI space below which a pixel is considered negative
- histomicstk.segmentation.positive_pixel_count.count_image(image, params, mask=None)[source]¶
Count positive pixels, computing a label mask and summary statistics.
- Parameters:
image (array-like) – NxMx3 array of RGB data
params (Parameters) – An instance of Parameters, which see for further documentation
mask (array-like) – A boolean mask. If present, only pixels where the mask is True are considered.
- Returns:
stats (Output) – Various statistics on the input image. See Output.
label_image (array-like) – NxM array of pixel types. See Labels for the different values.
- histomicstk.segmentation.positive_pixel_count.count_slide(slide_path, params, region=None, tile_grouping=256, make_label_image=False)[source]¶
Compute a count of positive pixels in the slide at slide_path. This routine can also create a label image.
- Parameters:
slide_path (string (path)) – Path to the slide to analyze.
params (Parameters) – An instance of Parameters, which see for further documentation
region (dict, optional) – A valid region dict (per a large_image TileSource.tileIterator’s region argument)
tile_grouping (int) – The number of tiles to process as part of a single task
make_label_image (bool, default=False) – Whether to make a label image. See also “Notes”
- Returns:
stats (Output) – Various statistics on the input image. See Output.
label_image (array-like, only if make_label_image is set)
Notes
The return value is either a single or a pair – it is in either case a tuple. Dask is used as configured to compute the statistics, but only if make_label_image is reset. If make_label_image is set, everything is computed in a single-threaded manner.