Realistic super-resolution image analysis for state of the art 2d contrast enhanced ultrasound imaging

An ultrasound based super-resolution algorithm was developed for clinical 2D ultrasound imaging in contrast enhanced ultrasound (CEUS) mode. Synthetic and in vivo data from sheep ovaries were used. Development involved microbubble-specific detection and segmentation, resulting in optimal localisation, resulting in an image analysis algorithm that could be used with clinical data of a few minutes duration. Microscopy images from histology slices were available to allow comparison of the in vivo vascular network with that produced from the processed ultrasound data. A 5-fold resolution gain was demonstrated in vessel width, as vessels slightly under 120 \mu \mathrm {m} were detected ( \lambda \quad = 257 \mu \mathrm {m}), while the synthetic data demonstrated that the microbubble (MB) localization uncertainty is 30 \mu \mathrm {m}. These results were achieved by processing video loops of under 2-minute duration. In conclusion, the above algorithm provided complete images of microvascular structure down to arteriole level from data that do not extend beyond a reasonable patient examination period.