Visibility-driven data filtering (VF) is a new method and algorithm for speeding up computationally expensive 3-dimensional convolution filters. The aim is to provide ultrasound companies with a way to implement more advanced filtering methods by reducing processing time.
The visibility filter (VF) rapidly identifies the region of interest in individual voxels and eliminates accompanying noise, providing a cleaner and clearer visualisation of a target area in real time. At present this remains the only visibility-based optimisation filter poised to enter the market.
This advancement represents a paradigm shift, as it is the only approach to reducing the enormous size of the data sets prior to further processing, thus reducing processor occupation and analysis time. This proprietary VF is an algorithm designed to be incorporated into the software, and may be retrofitted into installed software and purchased hardware, thus demonstrating ease of use.
Christian Michelsen Research (CMR)
Haukeland University Hospital
University of Bergen
Veronika Solteszova, Associate professor II, University of Bergen
Marine Ecosystem Technologies AS (METAS) provides technology solutions to subsea challenges within environmental monitoring, Active Acoustic Leak Detection oil and gas (AALD) as well as multipurpose subsea sensor solutions.