New Doppler-based imaging method in echocardiography with applications in blood/tissue segmentation

Sigve Hovda*, Håvard Rue, Bjørn Olstad

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Knowledge Based Imaging is suggested as a method to distinguish blood from tissue signal in transthoracial echocardiography. Parametric model for the autocorrelation functions for turbulent blood flow and slowly moving tissue are augmented for in this paper. The model also includes the presence of stationary clutter noise and system white noise. Knowledge Based Imaging utilizes the maximum likelihood function to classify blood and tissue signal. In amplitude imaging blood and tissue are separated by their difference in signal powers. This effect is also present in Knowledge Based Imaging. In addition, this method utilizes the fact that blood flow is turbulent and moves faster than tissue. Some images of Knowledge Based Imaging with different parameter settings are visually compared with Second-Harmonic Imaging, Fundamental Imaging and Bandwidth Imaging [1].

Original languageEnglish (US)
Title of host publicationMedical Imaging and Informatics - 2nd International Conference, MIMI 2007, Revised Selected Papers
Pages207-215
Number of pages9
DOIs
StatePublished - 2008
Externally publishedYes
Event2nd International Conference on Medical Imaging and Informatics, MIMI 2007 - Beijing, China
Duration: Aug 14 2007Aug 16 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4987 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd International Conference on Medical Imaging and Informatics, MIMI 2007
Country/TerritoryChina
CityBeijing
Period08/14/0708/16/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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