Point detection in textured ultrasound images

Stine Hverven Thon; Andreas Austeng; Roy Edgar Hansen

doi:10.1016/j.ultras.2023.106968

Point detection in textured ultrasound images

Ultrasonics. 2023 May:131:106968. doi: 10.1016/j.ultras.2023.106968. Epub 2023 Feb 24.

Authors

Stine Hverven Thon¹, Andreas Austeng², Roy Edgar Hansen³

Affiliations

¹ Department of Informatics, University of Oslo, P.O. Box 1080, Blindern, Oslo, NO-0316, Norway. Electronic address: stinemhv@ifi.uio.no.
² Department of Informatics, University of Oslo, P.O. Box 1080, Blindern, Oslo, NO-0316, Norway.
³ Department of Informatics, University of Oslo, P.O. Box 1080, Blindern, Oslo, NO-0316, Norway; Norwegian Defence Research Establishment (FFI), P.O. Box 25, Kjeller, NO-2027, Norway.

PMID: 36848822
DOI: 10.1016/j.ultras.2023.106968

Abstract

Detection of point scatterers in textured ultrasound images can be challenging. This paper investigates how four multilook methods can improve the detection. We analyze many images with known point scatterer locations and randomly textured backgrounds. The normalized matched filter (NMF) and multilook coherence factor (MLCF) methods are normalized methods that do not require any texture correction prior to detection analysis. They are especially propitious when optimal texture correction of the ultrasound images is difficult to obtain. The results show significant improvement in detection performance when the MLCF method is weighted with the prewhitened and texture corrected image. The method can be applied even when we do not have prior knowledge about the optimal prewhitening limits. The multilook methods NMF and NMF weighted (NMFW) are very favorable methods to apply on images where acoustic noise dominates the speckle background.

Keywords: Detection; Multilook; Point scatterer; Texture; Ultrasound; Whitening.