Standardisation of Convex Ultrasound Data Through Geometric Analysis and Augmentation

TL;DR

This paper introduces a novel geometric analysis method to standardize and augment convex ultrasound data by extracting the ultrasound plane using annulus sector geometry, aiming to improve data consistency and benchmarking.

Contribution

It proposes a new approach for ultrasound data standardization using geometric analysis and augmentation, addressing variability and sparsity issues in ultrasound imaging datasets.

Findings

Robustness validated on private and public datasets.

Effective extraction of ultrasound planes using annulus sector geometry.

Enhanced data standardization and augmentation demonstrated.

Abstract

The application of ultrasound in healthcare has seen increased diversity and importance. Unlike other medical imaging modalities, ultrasound research and development has historically lagged, particularly in the case of applications with data-driven algorithms. A significant issue with ultrasound is the extreme variability of the images, due to the number of different machines available and the possible combination of parameter settings. One outcome of this is the lack of standardised and benchmarking ultrasound datasets. The method proposed in this article is an approach to alleviating this issue of disorganisation. For this purpose, the issue of ultrasound data sparsity is examined and a novel perspective, approach, and solution is proposed; involving the extraction of the underlying ultrasound plane within the image and representing it using annulus sector geometry. An application of this methodology is proposed, which is the extraction of scan lines and the linearisation of convex planes. Validation of the robustness of the proposed method is performed on both private and public data. The impact of deformation and the invertibility of augmentation using the estimated annulus sector parameters is also studied. Keywords: Ultrasound, Annulus Sector, Augmentation, Linearisation.