Elastography using multi-stream GPU: An application to online tracked ultrasound elastography, in-vivo and the da Vinci surgical system

Nishikant P. Deshmukh, Hyun Jae Kang, Seth D. Billings, Russell H Taylor, Gregory Hager, Emad Boctor

Research output: Contribution to journalArticle

Abstract

A system for real-time ultrasound (US) elastography will advance interventions for the diagnosis and treatment of cancer by advancing methods such as thermal monitoring of tissue ablation. A multi-stream graphics processing unit (GPU) based accelerated normalized cross-correlation (NCC) elastography, with a maximum frame rate of 78 frames per second, is presented in this paper. A study of NCC window size is undertaken to determine the effect on frame rate and the quality of output elastography images. This paper also presents a novel system for Online Tracked Ultrasound Elastography (O-TRuE), which extends prior work on an offline method. By tracking the US probe with an electromagnetic (EM) tracker, the system selects in-plane radio frequency (RF) data frames for generating high quality elastograms. A novel method for evaluating the quality of an elastography output stream is presented, suggesting that O-TRuE generates more stable elastograms than generated by untracked, free-hand palpation. Since EM tracking cannot be used in all systems, an integration of real-time elastography and the da Vinci Surgical System is presented and evaluated for elastography stream quality based on our metric. The da Vinci surgical robot is outfitted with a laparoscopic US probe, and palpation motions are autonomously generated by customized software. It is found that a stable output stream can be achieved, which is affected by both the frequency and amplitude of palpation. The GPU framework is validated using data from in-vivo pig liver ablation; the generated elastography images identify the ablated region, outlined more clearly than in the corresponding B-mode US images.

Original languageEnglish (US)
Article numbere115881
JournalPLoS One
Volume9
Issue number12
DOIs
StatePublished - Dec 26 2014

Fingerprint

Elasticity Imaging Techniques
Ultrasonics
probes (equipment)
Ablation
Palpation
robots
radio
Electromagnetic Phenomena
hands
methodology
heat
Liver
liver
swine
neoplasms
Graphics processing unit
monitoring
Online Systems
Systems Integration
Tissue

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Elastography using multi-stream GPU : An application to online tracked ultrasound elastography, in-vivo and the da Vinci surgical system. / Deshmukh, Nishikant P.; Kang, Hyun Jae; Billings, Seth D.; Taylor, Russell H; Hager, Gregory; Boctor, Emad.

In: PLoS One, Vol. 9, No. 12, e115881, 26.12.2014.

Research output: Contribution to journalArticle

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