Compression Hurts, Pooling Helps: Information Loss in Rayleigh-Scale Estimation from B-Mode Ultrasound
Abstract
Clinical B-mode images are widely available as potential data sources for quantitative ultrasound (QUS) analysis for tissue characterization. However, standard clinical ultrasound devices apply unknown log-compression to RF envelope data before display and storage. Previous work has demonstrated estimation of the underlying RF envelope statistics in the presence of an unknown compression law. Using Fisher information analysis, we show that finite-offset log compression causes severe information loss when estimating the Rayleigh scale σ, which controls diffuse speckle. For a single image window, unknown compression raises the minimum achievable variance for unbiased estimation of σ by a compression-independent factor of approximately 34.98. When M equal-sized windows share the same unknown compression settings, the excess variance decays as 1/M; even in the most favorable regime, reducing the variance inflation factor below 1.1 requires 340 windows. Our analysis treats the contrast parameter a as unknown and the boundary offset b as known; estimating b experimentally shows even larger variance. We validate this theory using synthetic estimation experiments and demonstrate RF-scale recovery on real RF-envelope windows from the OASBUD dataset. Together, these results clarify the limitations of using routine B-mode images for QUS.
Related
- A New Extended Exponential Rayleigh Distribution: Estimation and Application
- A Sample-Based Approach for Hierarchical Information-Theoretic Compression of Probabilistic Occupancy Grids
- Dependency, Compression, and Synergy: A Unified Information-Theoretic View of Multimodal Learning
- Information Lower Bound for Regime Boundary Estimation — Optimal Precision Limit at the n² Scale and Universal Constant c=1/8 in the Fixed-Breakpoint Model
- Thyroid Nodule Segmentation in Ultrasound Images with Conformal Uncertainty Estimation
BibTeX
@misc{smith2026compression,
title = {{Compression Hurts, Pooling Helps: Information Loss in Rayleigh-Scale Estimation from B-Mode Ultrasound}},
author = {D. Hudson Smith and Ahmer Raza},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2609.19525},
eprint = {2609.19525},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.19525},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Compression Hurts, Pooling Helps: Information Loss in Rayleigh-Scale Estimation from B-Mode Ultrasound
AU - D. Hudson Smith
AU - Ahmer Raza
PY - 2026
DA - 2026/10/09
PB - arXiv
DO - 10.48550/arxiv.2609.19525
UR - https://arxiv.org/abs/2609.19525
AB - Clinical B-mode images are widely available as potential data sources for quantitative ultrasound (QUS) analysis for tissue characterization. However, standard clinical ultrasound devices apply unknown log-compression to RF envelope data before display and storage. Previous work has demonstrated estimation of the underlying RF envelope statistics in the presence of an unknown compression law. Using Fisher information analysis, we show that finite-offset log compression causes severe information loss when estimating the Rayleigh scale σ, which controls diffuse speckle. For a single image window, unknown compression raises the minimum achievable variance for unbiased estimation of σ by a compression-independent factor of approximately 34.98. When M equal-sized windows share the same unknown compression settings, the excess variance decays as 1/M; even in the most favorable regime, reducing the variance inflation factor below 1.1 requires 340 windows. Our analysis treats the contrast parameter a as unknown and the boundary offset b as known; estimating b experimentally shows even larger variance. We validate this theory using synthetic estimation experiments and demonstrate RF-scale recovery on real RF-envelope windows from the OASBUD dataset. Together, these results clarify the limitations of using routine B-mode images for QUS.
ER -