Full-reference image quality assessment-based B-mode ultrasound image similarity measure
This work addresses the unsolved issue of ultrasound image similarity measurement for applications like quality assessment and abnormal region detection, but it is incremental as it builds on existing full-reference methods.
The paper tackled the problem of measuring similarity in B-mode ultrasound images, which is challenging due to speckle noise, by conducting a comparative study of full-reference image quality assessment methods and proposing a similarity-based motion tracking re-initialization framework; the result showed a reduction in mean tracking error from 2 mm to about 1.5 mm in ultrasound liver sequences.
During the last decades, the number of new full-reference image quality assessment algorithms has been increasing drastically. Yet, despite of the remarkable progress that has been made, the medical ultrasound image similarity measurement remains largely unsolved due to a high level of speckle noise contamination. Potential applications of the ultrasound image similarity measurement seem evident in several aspects. To name a few, ultrasound imaging quality assessment, abnormal function region detection, etc. In this paper, a comparative study was made on full-reference image quality assessment methods for ultrasound image visual structural similarity measure. Moreover, based on the image similarity index, a generic ultrasound motion tracking re-initialization framework is given in this work. The experiments are conducted on synthetic data and real-ultrasound liver data and the results demonstrate that, with proposed similarity-based tracking re-initialization, the mean error of landmarks tracking can be decreased from 2 mm to about 1.5 mm in the ultrasound liver sequence.