Particle filtering for robust modal identification and sediment sound speed estimation

2014 ◽  
Vol 136 (4) ◽  
pp. 2085-2085
Author(s):  
Nattapol Aunsri ◽  
Zoi-Heleni Michalopoulou
Keyword(s):  
Particle Filtering ◽  
Sound Speed ◽  
Modal Identification ◽  
Speed Estimation

Ultrasonic Adaptive Sound Speed Estimation for the Diagnosis and Quantification of Hepatic Steatosis: A Pilot Study

2018 ◽  
Vol 40 (06) ◽  
pp. 722-733 ◽  
Author(s):  
Marco Dioguardi Burgio ◽  
Marion Imbault ◽  
Maxime Ronot ◽  
Alex Faccinetto ◽  
Bernard E. Van Beers ◽  
...  
Keyword(s):  
Hepatic Steatosis ◽  
Sound Speed ◽  
Validation Cohort ◽  
Liver Steatosis ◽  
Receiver Operating Curve ◽  
Coefficient Of Determination ◽  
Proton Density ◽  
Speed Estimation ◽  
Training Cohort ◽  
Receiver Operating Curve Analysis

Abstract Purpose To evaluate the ability of a new ultrasound (US) method based on sound speed estimation (SSE) with respect to the detection, quantification, and grading of hepatic steatosis using magnetic resonance (MR) proton density fat fraction (PDFF) as the reference standard and to calculate one US fat index based on the patient’s SSE. Materials and Methods This study received local IRB approval. Written informed consent was obtained from patients. We consecutively included N = 50 patients as the training cohort and a further N = 50 as the validation cohort who underwent both SSE and abdominal MR. Hepatic steatosis was classified according to MR-PDFF cutoffs as: S0 ≤ 6.5 %, S1 6.5 to 16.5 %, S2 16.5 to 22 %, S3 ≥ 22 %. Receiver operating curve analysis was performed to evaluate the diagnostic performance of SSE in the diagnosis of steatosis (S1–S3). Based on the optimal data fit derived from our study, we proposed a correspondence between the MR-PDFF and a US fat index. Coefficient of determination R2 was used to evaluate fit quality and was considered robust when R2 > 0.6. Results The training and validation cohorts presented mean SSE values of 1.570 ± 0.026 and 1.568 ± 0.023 mm/µs for S0 and 1.521 ± 0.031 and 1.514 ± 0.019 mm/µs for S1–S3 (p < 0.01) patients, respectively. An SSE threshold of ≤ 1.537 mm/µs had a sensitivity of 80 % and a specificity of 85.7 % in the diagnosis of steatosis (S1-S3) in the training cohort. Robust correspondence between MR-PDFF and the US fat index was found both for the training (R2 = 0.73) and the validation cohort (R2 = 0.76). Conclusion SSE can be used to detect, quantify and grade liver steatosis and to calculate a US fat index.

scholarly journals Ultrasonic fat fraction quantification using in vivo adaptive sound speed estimation

2018 ◽  
Vol 63 (21) ◽  
pp. 215013 ◽  
Author(s):  
Marion Imbault ◽  
Marco Dioguardi Burgio ◽  
Alex Faccinetto ◽  
Maxime Ronot ◽  
Hanna Bendjador ◽  
...  
Keyword(s):  
Sound Speed ◽  
Speed Estimation ◽  
Fat Fraction

An evaluation of an in vivo local sound speed estimation technique by the crossed beam method

1990 ◽  
Vol 16 (1) ◽  
pp. 65-72 ◽  
Author(s):  
Masafumi Kondo ◽  
Kinya Takamizawa ◽  
Makoto Hirama ◽  
Kiyoshi Okazaki ◽  
Kazuhiro Iinuma ◽  
...  
Keyword(s):  
Sound Speed ◽  
Speed Estimation ◽  
Estimation Technique ◽  
Beam Method ◽  
Local Sound

Bayesian modal identification with particle filtering for sediment property inversion

2017 ◽  
Vol 141 (5) ◽  
pp. 3471-3471
Author(s):  
Zoi-Heleni Michalopoulou ◽  
Andrew Pole ◽  
Nattapol Aunsri
Keyword(s):  
Particle Filtering ◽  
Modal Identification ◽  
Sediment Property

Pulse-echo sound speed estimation using second order speckle statistics

2012 ◽  
Author(s):  
Ivan M. Rosado-Mendez ◽  
Kibo Nam ◽  
Ernest L. Madsen ◽  
Timothy J. Hall ◽  
James A. Zagzebski
Keyword(s):  
Sound Speed ◽  
Second Order ◽  
Speed Estimation ◽  
Pulse Echo
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