3D organ property mapping using freehand ultrasound scans

Abstract

3D organ property mapping has gained a considerable amount of interest in the recent years because of its diagnostic and clinical significance. Existing methods for 3D property mapping include computed tomography (CT), magnetic resonance imaging (MRI), and 3D ultrasound (3DUS). These methods, while capable of producing 3D maps, suffer from one or more of the following drawbacks: high cost, long scan times, computational complexity, use of ionizing radiation, lack of portability, and the need for bulky equipment. We propose the development of a framework that allows for the creation of 3D property maps at point of care (specifically structure and speed of sound). A fusion of multiple low-cost sensors in a Bayesian framework localizes a conventional 1D-ultrasound probe with respect to the room or the patient's body; localizing the probe relative to the body is achieved by using the patient's superficial vasculature as a natural encoding system. Segmented 2D ultrasound images and quantitative 2D speed of sound maps obtained using numeric inversion are stitched together to create 3D property maps. A further advantage of this framework is that it provides clinicians with dynamic feedback during freehand scans; specifically, it dynamically updates the underlying structural or property map to reflect high and low uncertainty regions. This allows clinicians to repopulate regions within additional scans. Lastly, the method also allows for the registration and comparison of longitudinally acquired 3D property/structural maps.