Confidence estimation in IVUS radio-frequency data with random walks

The shadow regions in ultrasound (US) B-mode images are due to severe reflection of backscattered signals from dense tissue/medium interface. The loss of ultrasound energy as well as lack of textural or spectral features in these regions raise uncertainty, resulting confusion among experts decisions and developed computer-aided diagnosis (CAD) algorithms outcomes. In this paper, we present a novel uncertainty (confidence) estimation method, modeling the problem through random walk under particular constrains motivated by underlying physics of ultrasound. We demonstrate that constructed confidence maps can then be employed in different ultrasound based CAD algorithms, which ultimately improve experts qualitative and quantitative assessments. We evaluate our method on intravascular ultrasound (IVUS) radiofrequency (RF) data and quantify the results through non-linearly registered histology image as ground-truth.