5 accepted papers
Sparse and low-rank decomposition, also known as robust principle component analysis, has been applied successfully in numerous applications. Typically, this approach leads to a minimization problem which is solved using iterative algorithms. Drawing inspiration from recurrent networks, in recent ye…
Based on the intravascular infusion of gas microbubbles, which act as ultrasound contrast agents, ultrasound localization microscopy has enabled super resolution vascular imaging through precise detection of individual microbubbles across numerous imaging frames. However, analysis of high-density re…
Ultrasound localization microscopy offers new radiation-free diagnostic tools for vascular imaging deep within the tissue. Despite its high spatial resolution, low microbubble concentrations dictate the acquisition of tens of thousands of images, over the course of several seconds to tens of seconds…
The iterative linear expansion of threshold framework, or iLET, offers a new approach for solving image restoration problems under sparsity assumptions. Instead of estimating the reconstructed image directly, the iLET paradigm parametrizes the reconstruction process as a linear combination of elemen…
Traditionally, spatial resolution in optical imaging is limited by diffraction. Although sub-wavelength information is absent in the measurements, state-of-the-art fluorescence based localization techniques such as PALM and STORM manage to achieve spatial resolution of tens of nano-meters, but with…