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 D. Hager, Emad M. Boctor, Assad Anshuman Oberai
2014 PLoS ONE  
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
more » ... mages. 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.
doi:10.1371/journal.pone.0115881 pmid:25541954 pmcid:PMC4277422 fatcat:5bwsbqcp4ja7bh3fpp3ddhp7wq