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Special Collection: Super Resolution
Optimizing Sensitivity of Ultrasound Contrast-Enhanced Super-Resolution Imaging by Tailoring Size Distribution of Microbubble Contrast Agent
Ultrasound contrast-enhanced super-resolution imaging has recently attracted attention because of its extraordinary ability to image vascular features much smaller than the ultrasound diffraction limit. This method requires sensitive detection of separable microbubble events despite a noisy tissue background to indicate the microvasculature, and any approach that could improve the sensitivity of the ultrasound system to individual microbubbles would be highly beneficial. In this study, we evaluated the effect of varying microbubble size on super-resolution imaging sensitivity.Super-Resolution Image Reconstruction Using Diffuse Source Models
Image reconstruction is central to many scientific fields, from medical ultrasound and sonar to computed tomography and computer vision. Although lenses play a critical reconstruction role in these fields, digital sensors enable more sophisticated computational approaches. A variety of computational methods have thus been developed, with the common goal of increasing contrast and resolution to extract the greatest possible information from raw data. This paper describes a new image reconstruction method named the Diffuse Time-domain Optimized Near-field Estimator (dTONE).Pixel Compounding: Resolution-Enhanced Ultrasound Imaging for Quantitative Analysis
Accurate measurement of structural features represented in medical images is important in clinical trials and patient diagnosis. A key factor for precision is spatial resolution, which in ultrasonic imaging is limited by transducer array arrangements, transmitting frequency, and data acquisition firmware. In this paper, a variation of pixel compounding is proposed to enhance ultrasound resolution using acquired cine loops. The technique operates on a sequence of ultrasound B-scan images acquired with random motion.
