Multicycle Temporal Compounding Sonography for Despeckling at Specified Respiratory Phases

This work presents a breath-hold-free abdominal ultrasound method for both clinical and ICU settings, addressing speckle noise and motion artifacts. Its key contribution lies in respiratory phase-guided multicycle temporal compounding - identifying motion states across cycles to fuse images for target despeckling. A synergistic framework combines detail-preserving anisotropic diffusion (for speckle removal) and guided filtering (for structure transfer), while the outputs progressively refine as acquisition proceeds. Evaluated on 31 ventilator-assisted and 66 spontaneous respiration datasets, the method achieved average $\beta =0.931$ /0.930, the speckle suppression and mean preservation index (SMPI) of 0.483/0.584, and the Pratt's figure of merit 0.842/0.827, outperforming prevalent despeckling methods in edge preservation and despeckling. With computational efficiency (~2.65s/iteration) comparable to established methods and applicability across respiration styles, it enables reliable motion-artifact-suppressed imaging without breath-holding, streamlining abdominal US workflows in critical care and routine practice.

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Publication Details

Journal
IEEE Transactions on Medical Imaging
Published
2025-08-25
DOI
https://doi.org/10.1109/tmi.2025.3602633
Primary Topic
Ultrasound in Clinical Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Multicycle Temporal Compounding Sonography for Despeckling at Specified Respiratory Phases

Juan Tu, Chuhao Yin, Xiasheng Guo, Dong Zhang et al.
IEEE Transactions on Medical Imaging
Ultrasound in Clinical Applications
article

Multicycle Temporal Compounding Sonography for Despeckling at Specified Respiratory Phases

Juan Tu, Chuhao Yin, Xiasheng Guo, Dong Zhang, Yiyun Wu, Fansong Dong
article en

Abstract

This work presents a breath-hold-free abdominal ultrasound method for both clinical and ICU settings, addressing speckle noise and motion artifacts. Its key contribution lies in respiratory phase-guided multicycle temporal compounding - identifying motion states across cycles to fuse images for target despeckling. A synergistic framework combines detail-preserving anisotropic diffusion (for speckle removal) and guided filtering (for structure transfer), while the outputs progressively refine as acquisition proceeds. Evaluated on 31 ventilator-assisted and 66 spontaneous respiration datasets, the method achieved average $\beta =0.931$ /0.930, the speckle suppression and mean preservation index (SMPI) of 0.483/0.584, and the Pratt's figure of merit 0.842/0.827, outperforming prevalent despeckling methods in edge preservation and despeckling. With computational efficiency (~2.65s/iteration) comparable to established methods and applicability across respiration styles, it enables reliable motion-artifact-suppressed imaging without breath-holding, streamlining abdominal US workflows in critical care and routine practice.

IEEE Transactions on Medical ImagingVol. 45(2)
Institute of Acoustics (CN), Collaborative Innovation Center of Advanced Microstructures (CN), Nanjing University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 74%
Ultrasound in Clinical Applications
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