Tauhidul Islam

TL;DR: A new two-step EPR estimation technique based on dynamic programming elastography (DPE) and Horn-Schunck optical flow estimation that provides EPR elastograms of higher quality and accuracy than those produced by AM and CM.

TL;DR: This paper presents a novel self-supervised feature learning method by effectively exploiting multi-modal data for retinal disease diagnosis by synthesizing the corresponding FFA modality and formulating a patient feature-based softmax embedding objective.

TL;DR: This paper developed a new method to simultaneously reconstruct YM and PR of a tumor and of its surrounding tissues based on the assumptions of axisymmetry and ellipsoidal-shape inclusion, which allows the generation of high spatial resolution Ym and PR maps from axial and lateral strain data obtained via ultrasound elastography.

TL;DR: Several standard objective measures and subjective evaluations show that the proposed method outperforms some of the state-of-the-art speech enhancement methods at high as well as low levels of SNRs.

TL;DR: The availability of the analytical model and solutions presented in this paper may be useful to estimate diagnostically relevant poroelastic parameters such as interstitial permeability and fluid pressure, and, in general, for a better interpretation of clinically-relevant ultrasound elastography results.