Fast multi-scale edge-detection in medical ultrasound signals

TL;DR

This paper introduces a fast multi-scale edge detection method for medical ultrasound signals using wavelet transform maxima-lines, achieving reliable detection of significant features with reduced computational effort.

Contribution

A novel, efficient multi-scale edge detection algorithm based on wavelet maxima-lines tailored for medical ultrasound signals, balancing speed and reliability.

Findings

Effectively detects major features in ultrasound signals

Identifies low-contrast edges reliably

Reduces computational time significantly

Abstract

In this article we suggest a fast multi-scale edge-detection scheme for medical ultrasound signals. The edge-detector is based on well-known properties of the continuous wavelet trans- form. To achieve both good localization of edges and detect only significant edges, we study the maxima-lines of the wavelet transform. One can obtain the maxima-lines between two scales by computing the wavelet transform at several intermediate scales. To reduce computational effort and time we suggest a time-scale filtering procedure which uses only few scales to connect modulus-maxima across time-scale plane. The design of this procedure is based on a study of maxima-lines corresponding to edges typical for medical ultrasound signals. This study allows us to construct an algorithm for medical ultrasound signals which meets the demand for speed, but not on expense of reliability. The edge-detection algorithm has been applied to a large class of medical ultrasound sig- nals including tumour-, liver- and artery-images. Our results show that the proposed algorithm effectively detects major features in such signals, including edges with low contrast.