ultrasound_metrics.metrics.cnr#
Contrast-to-Noise Ratio (CNR) metric for ultrasound image quality assessment.
Functions#
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Compute the contrast-to-noise ratio (CNR) between two regions. |
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Get backend-agnostic aggregation function. |
Module Contents#
- ultrasound_metrics.metrics.cnr.compute_cnr(
- values_signal: ultrasound_metrics._utils.array_api.ArrayAPIObj,
- values_noise: ultrasound_metrics._utils.array_api.ArrayAPIObj,
- fun_signal: str = 'MEAN',
- fun_noise: str = 'MEAN',
- *,
- use_signal_variance: bool = True,
- use_noise_variance: bool = True,
Compute the contrast-to-noise ratio (CNR) between two regions.
The CNR is commonly used in medical ultrasound to assess image quality [1]. The CNR is computed as [2]:
\[CNR = \frac{|\mu_i - \mu_o|}{\sqrt{\sigma_i^2 + \sigma_o^2}}\]where:
\[ \begin{align}\begin{aligned}\mu_i = E\{|s_i|^2\}\\\mu_o = E\{|s_o|^2\}\\\sigma_i^2 = E\{(|s_i|^2 - \mu_i)^2\}\\\sigma_o^2 = E\{(|s_o|^2 - \mu_o)^2\}\end{aligned}\end{align} \]with \(s_i\) and \(s_o\) representing the signal values inside and outside the region of interest, respectively.
- Parameters:
values_signal – Pixel values from the signal region (e.g., inside a lesion).
values_noise – Pixel values from the noise/background region (e.g., outside a lesion).
fun_signal – Aggregation function for the signal region (“MEAN” or “MEDIAN”).
fun_noise – Aggregation function for the noise region (“MEAN” or “MEDIAN”).
use_signal_variance – Whether to include signal variance in the denominator.
use_noise_variance – Whether to include noise variance in the denominator.
- Returns:
The contrast-to-noise ratio.
- Return type:
References
- ultrasound_metrics.metrics.cnr.get_agg_func(
- xp: ultrasound_metrics._utils.array_api.ArrayAPIObj,
- name: str,
Get backend-agnostic aggregation function.
- Parameters:
xp – Array API namespace.
name – Name of aggregation function (‘MEAN’ or ‘MEDIAN’).
- Returns:
Aggregation function.
- Return type:
callable