Zoom is Meaningful: Discerning Ultrasound Images' Zoom Levels

Mohammad Alsharid, Robail Yasrab, Md. Mostafa Kamal Sarker, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble

Abstract: The paper explores the use of an under-utilised piece of information extractable from fetal ultrasound images, ‘zoom’. In this paper, we explore the obtainment of zoom information and conclude with a couple of potential use cases for it. We make the case that zoom information is meaningful and that convolutional neural networks can distinguish between the different zoom levels that images were acquired at, even if images were manipulated post-acquisition.