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BSRPCA: A Simplified Blind Super-Resolved RPCA-Based Approach for Enhancing Blood Flow Estimation

Year: 2025

Type: conference-paper

Abstract: Ultrasound Localization Microscopy (ULM) offers great advances compared to conventional ultrasound imaging, enabling the reconstruction of microvascular structures with micrometer-scale precision. Most model-based localization approaches for ULM rely on a sequential five-step framework, which complicates parameter tuning and results in intricate tissue filtering. In addition, insufficient consideration of point spread function (PSF) also affects the final results. End-to-end data-driven solutions offer promising results yet require training data and ground-truths. In this study, we introduced a novel approach, based on computational super-resolution referred to as BSRPCA - Blind Super-Resolved Robust Principal Component Analysis, to address these challenges. Our method replaces the first three steps of the ULM process with a single super-resolution step. Experimental results on both in silico and in vivo datasets have proven the effectiveness of our method compared to the other benchmarks.

Source: Proceedings - International Conference on Image Processing

DOI: 10.1109/icip55913.2025.11084341

Authors: Xuan-Hieu Le, Jean-Pierre Remeniéras, Denis Kouamé, Duong-Hung Pham

Institutions: Centre National de la Recherche Scientifique, Institut de Recherche en Informatique de Toulouse, Université de Tours, Inserm, Imaging, Brain, and Neuropsychiatry

Language: English

Topic: Photoacoustic and Ultrasonic Imaging

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: Institut National de la Santé et de la Recherche Médicale, TINE

OpenAlex ID: W4413278591

FWCI:

Cites: 18

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Related to: 10