Title

Fasu: A Full Automatic Segmenting System For Ultrasound Images

Keywords

Active contours; Computer science; Equations; Filters; Image segmentation; Noise reduction; Smoothing methods; Speckle; Spline; Ultrasonic imaging

Abstract

In this paper, we propose a novel segmenting system for ultrasound images. This solution is separated into three steps. First, we filter noise by using the "peak-and-valley" with scanning pixels along the Hilbert curve. Then we use the "Cubic Spline Interpolation" between local peaks and valleys to smooth the image. Second, we present windows adaptive threshold, to eliminate trial and error, as the method for obtaining the right threshold for beginning segmentation. Third, we label distinct, disconnected objects and use our "core area" to detect the object of interest based on the feature knowledge bases. Our method was experimented with liver ultrasound images. We compared the orientation and centroid feature vectors of our Full Automatic Segmenting Ultrasound (FASU) method with the manual segmentation method. The results are fully automatic and confirm the accuracy of our FASU method.

Publication Date

1-1-2002

Publication Title

Proceedings of IEEE Workshop on Applications of Computer Vision

Volume

2002-January

Number of Pages

90-94

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/ACV.2002.1182163

Socpus ID

79960027444 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/79960027444

This document is currently not available here.

Share

COinS