A Novel 2x2D Radial Basis Function-Based Interpolation for Short Acquisition Time and Relaxed Frame Rate Ultrasound Localization Microscopy

Abstract

Ultrasound localization microscopy (ULM) has become a potent technique for microvascular imaging using ultrasound waves. However, one major challenge is the high frame rate and lengthy acquisition time needed to produce super-resolved (SR) images. To overcome this, our goal is to relax the frame rate and shorten this acquisition time while preserving SR image quality, thereby enhancing ULM’s clinical applicability. To this end, we propose two distinct strategies: first, we suggest acquiring the data at lower frame rate followed by applying the reconstruction technique to compensate the lost information due to low frame rate imaging. Second, to tackle the prolonged acquisition time, we propose compressing acquisition time by a compression ratio (CR), which can degrade SR image quality due to reduced temporal information. To mitigate this, we temporally upsample the in-phase-quadrature (IQ) data by a factor equal to the CR after compressed acquisition. In addition, we introduce a novel bidirectional (2x2D) interpolation (IP) using radial basis function (RBF)-based reconstruction to estimate unknown values in the 3D IQ data (x–z–t), thereby enhancing temporal resolution. The rationale behind using 2x2D IP is its ability to integrate spatiotemporal information from two orthogonal x–t and z–t planes, effectively addressing anisotropies and nonuniformities in microbubble motion. This 2x2D approach improves the reconstruction of microbubbles’ dynamics by interpolating along both the x- and z-directions. The method was tested on rat brain and rat kidney datasets recorded at 1 kHz, demonstrating relaxing the frame rate to 100 Hz (using the first strategy) and a reduction in acquisition time by a factor of 3 to 4 (using the second strategy) while maintaining SR image quality comparable to the original uncompressed data, including density and velocity maps.