gms | German Medical Science

GMDS 2013: 58. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

01. - 05.09.2013, Lübeck

Advanced channel-data signal processing in multimodal ultrasound imaging

Meeting Abstract

  • Marc Fournelle - Fraunhofer - Institut für Biomedizinische Technik IBMT, Sankt Ingbert, DE
  • Wolfgang Bost - Fraunhofer - Institut für Biomedizinische Technik IBMT, Sankt Ingbert, DE
  • Holger Hewener - Fraunhofer - Institut für Biomedizinische Technik IBMT, Sankt Ingbert, DE
  • Steffen Tretbar - Fraunhofer - Institut für Biomedizinische Technik IBMT, Sankt Ingbert, DE

GMDS 2013. 58. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Lübeck, 01.-05.09.2013. Düsseldorf: German Medical Science GMS Publishing House; 2013. DocAbstr.333

doi: 10.3205/13gmds264, urn:nbn:de:0183-13gmds2649

Published: August 27, 2013

© 2013 Fournelle et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.



Introduction: In the last decade, advances in ultrasound electronics have led to a paradigm shift regarding the way ultrasound data are processed, stored and visualized. Conventional medical end-user devices were based on a complete analogue signal processing chain for reconstruction and processing of the ultrasound channel data (voltage signals from individual ultrasound array elements). Accordingly, only the final result of the processing i.e. the reconstructed B-scan image was provided to the user and could be stored as image or reconstructed RF-data. However, for special ultrasound applications such as multimodal imaging, optoacoustic imaging or techniques involving complex transmitted signal shapes (matched filter or coded excitation strategies), more flexible hardware platforms allowing to retrieve data at several moments in the signal processing chain are necessary.

Materials and Methods: DiPhAS (Digital Phased Array System, Fraunhofer IBMT) is a state-of-the-art ultrasound research platform that enables the usage of arbitrary shaped transmission pulses and gives access to all data types from channel signals to reconstructed image data and further allows to adapt hardware parameters online using a closed-loop system architecture. Such a flexible hardware concept gives access to new ultrasound applications with special requirements that cannot be fulfilled with commercial standard systems. For instance, optoacoustic imaging is based on generation of broad-band acoustic signals after illumination of biological samples by short laser-pulses. It therefore allows to image biological structures with optical contrast and acoustical resolution. Since optical properties of different tissue chromophores strongly vary as a function of the optical wavelength, functional imaging (e.g. differentiation of arterial and venous blood) can be performed when using suitable algorithms. However, when optoacoustic imaging is performed using multielement array transducers, a hardware with channel data access is necessary as well as adequate reconstruction and processing algorithms.

Results: We have developed advanced reconstruction and filtering algorithms that can be applied to optoacoustic data in order to retrieve qualitative and quantitative information from in-vivo measurements for analysis of vessel morphology or function. In-vivo data of subcutaneous vasculature was acquired with DiPhAS for evaluation of the algorithms. Our flexible hardware configurations further allow multimodal imaging combining ultrasound with other clinically established modalities. A MRI-compatible version of the DiPhAS hardware has been developed for tracking of motion artefacts. Fast acquisition and processing of ultrasound B-scan data have been used in conjunction with pattern-recognition algorithms for triggering of MRI data acquisition. Based on the calculated displacement vectors of inner organs, the breathing cycle could be monitored for phase-adjusted acquisition of MRI-images.

Discussion: The potential of using advanced processing algorithms for enhancement of image quality in ultrasound-based diagnostic imaging has been demonstrated through the examples of optoacoustic techniques and ultrasound guided MRI. Further examples involving ultrasound parameter extraction in applications such as bone thickness measurements have further highlighted the benefits of advanced ultrasound processing algorithms for medical applications.