ArticleIEEE transactions on medical imaging2026
Fast 3-D Ultrasound Localization Microscopy via Projection-Based Processing Framework.
Article in IEEE transactions on medical imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Quantum-enhanced deep learning for elastographic image-based characterization of cutaneous and subcutaneous masses.Frontiers in medicine · 2026Article
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13 authors.
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Abstract
Three-dimensional ultrasound localization microscopy (ULM) enables comprehensive visualization of the vasculature, thereby improving diagnostic reliability. Nevertheless, its clinical translation remains challenging, as the exponential growth in voxel count for full 3D reconstruction imposes heavy computational demands and extensive post-processing time. In this row-column array (RCA)-based 3D in vivo pig kidney ULM study, we reformulate each step of the full 3D ULM pipeline, including beamforming, clutter filtering, motion estimation, microbubble separation and localization into a series of computational-efficient 2D operations, substantially reducing the number of voxels to be processed while maintaining comparable accuracy. The proposed framework reconstructs each 0.75-s ensemble acquired at volume rate of 400 Hz, covering a $25\times {27}.{4}\times {27}.{4}$ mm
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.