Filtering Super-Resolution Scan Conversion of Medical Ultrasound Frames

Abstract

In this paper, we consider a challenging problem of reconstruction of high resolution (HR) B-mode ultrasound (US) image by proposing a novel multi-frame based super-resolution (SR) scan conversion framework. This new framework of SR scan conversion reconstructs an improved HR frame by using the scan data of several low resolution (LR) frames. It also unifies the speckle reduction and HR scan conversion in such a way that it has become a single operation to generate a super-resolved image with lesser loss of information. We evaluated the performance of the proposed model on synthetic images, ultrasound simulated (by Field II software) images and real ultrasound image dataset and the comparison is performed against some of the publicly available state-of-the-art ultrasound image enhancement techniques. Significant improvement in image quality has been achieved due to utilization of non-redundant information present in the scan data of the LR frames. We demonstrate the improvement of the proposed technique through the computation of perceptual and quantitative quality metrics, such as, SSIM, PSNR etc. over the recent competing methods.