Elavisu

Elavisu: multi-platform ultrasonic imaging software

 

Elavisu is a medical imaging software aimed at radiologists. It focuses mainly on soft tissue elasticity estimation from ultrasonic images, or elastography. 

The main application of elastography is the detection and characterization of tumours in soft tissues, which helps with diagnosis of diseases such as cancer. The goal of the Elavisu project is to promote elastography and its applications among radiologists and medical institutions.

 

Research Background

Elavisu is based on the research work accomplished by the ultrasonic imaging team of CREATIS in the field of motion estimation (measurement) in ultrasonic image sequences. This work is innovative in the fields of:

-         Estimation of anatomically complex motion (see [1], [2], [3])

-         Real time estimation of very small (subpixelic) motion (see [4], [5], [6])

These two motion characteristics are very specific to soft tissues compression models and to the anatomic complexity of soft tissues.

 

Features

Elavisu can run in both online and offline modes:

-         Online mode for live visualization and analysis of ultrasonic data, directly from the echograph.

-         Offline visualization and post-treatment of recorded sequences.

Estimation of displacement and strain (see [7]) on a full sequence, or in one of several regions of interest.

Saving and loading of image sequences, including DICOM files.

Open architecture and ability to easily add new features to the software.

 

Images and videos

Elavisu's main window. Top left: B-Mode image (input). Top right: displacement of the probe. Bottom left: strain image and user-selected regions of interest. Bottom right: mean strain in the regions of interest.

 

Download:

Windows version. 1/Execute the installer. 2/Run Elavisu. 3/From the GUI select File Open demo file 'demo01.rf' in data_demo. 

 

Using Elavisu on an ultrasound phantom.

 

Team

Project leader : Philippe Delachartre

Developers : Laurent Guigues, Tanguy Maltaverne, Andre Machado, Laurent Favreau, Eduardo Davila

 

References

  1. BASA-09c. Basarab A, Lyshchik A, Grava C, Buzuloiu V, Delachartre P. Ultrasound image sequence registration and its application for thyroid nodular disease. J Signal Proces Syst. 2009 ;55:127-137.
  2. BASA-08c. Basarab A, Lyshchik A, Delachartre P. Multi-frame motion estimation for freehand elastography and its application to thyroid tumor imaging. In: IEEE ISBI. IEEE ISBI. Paris, France; 2008. pp. 532-535.
  3. BASAR-08a. Basarab A, Liebgott H, Morestin F, Lyshchik A, Higashi T, Asato R, Delachartre P. A method for vector displacement estimation with ultrasound images and its application for thyroid nodular disease. Med Image Anal. 2008 ;12:259-274.
  4. BASAR-09b. Basarab A, Gueth P, Liebgott H, Delachartre P. Phase-based block matching applied to motion estimation with unconventional beamforming strategies. IEEE Trans Ultrason Ferroelectr Freq Control. 2009 ;56:945-957.
  5. BASAR-09a. Basarab A, Liebgott H, Delachartre P. Analytic estimation of subsample spatial shift using the phases of multidimensional analytic signals. IEEE Trans Image Proces. 2009 ;18:440-447.
  6. BASAR-07a. Basarab A, Gueth P, Liebgott H, Delachartre P. Two-dimensional least-squares estimation for motion tracking in ultrasound elastography. In: IEEE EMBC. IEEE EMBC. Lyon, France; 2007. pp. 2155-2158.
  7. OLLI-10. Ollivier J, Lyshchik A, Basarab A, Delachartre P. A 2D least square differentiation filter for tensorial elastography. In: IEEE International Ultrasonics Symposium. IEEE International Ultrasonics Symposium. San Diego, USA; 2010. pp. 1624 - 1627.