TY - GEN
T1 - Quantitative Evaluation Method for Liver Fibrosis in Clinical Ultrasound B-Mode Image Based on Optimized Multi-Rayleigh Model
AU - Mori, Shohei
AU - Hirata, Shinnosuke
AU - Yamaguchi, Tadashi
AU - Hachiya, Hiroyuki
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/17
Y1 - 2018/12/17
N2 - We have proposed an evaluation method for liver fibrosis using an ultrasound B-mode image. We proposed a multi-Rayleigh (MRA) distribution model to express a probability density function of ultrasound echo envelope obtained from a fibrotic liver tissue. The MRA model enabled us to estimate quantitative liver fibrosis parameters such as amount of fibrotic tissue and fibrosis progressive ratio, and to quantitatively visualize the fibrotic tissue in the B-mode image. In previous studies, we addressed several challenges to quantitatively and correctly evaluate liver fibrosis using the MRA model in clinical condition. In the present study, we integrated past achievements as the optimized MRA model and evaluated the clinical ultrasound B-mode image of fibrotic liver. Using the optimized MRA model, the change of estimated fibrotic tissue characteristics according to the liver fibrosis stage well reflected the tissue structural change caused by liver fibrosis. We concluded that the fibrotic tissue characteristics can be quantitatively and correctly estimated in clinical condition by using the optimized MRA model.
AB - We have proposed an evaluation method for liver fibrosis using an ultrasound B-mode image. We proposed a multi-Rayleigh (MRA) distribution model to express a probability density function of ultrasound echo envelope obtained from a fibrotic liver tissue. The MRA model enabled us to estimate quantitative liver fibrosis parameters such as amount of fibrotic tissue and fibrosis progressive ratio, and to quantitatively visualize the fibrotic tissue in the B-mode image. In previous studies, we addressed several challenges to quantitatively and correctly evaluate liver fibrosis using the MRA model in clinical condition. In the present study, we integrated past achievements as the optimized MRA model and evaluated the clinical ultrasound B-mode image of fibrotic liver. Using the optimized MRA model, the change of estimated fibrotic tissue characteristics according to the liver fibrosis stage well reflected the tissue structural change caused by liver fibrosis. We concluded that the fibrotic tissue characteristics can be quantitatively and correctly estimated in clinical condition by using the optimized MRA model.
KW - liver fibrosis
KW - multi-Rayleigh model
KW - Rayleigh distribution
KW - speckled pattern
KW - tissue characterization
UR - http://www.scopus.com/inward/record.url?scp=85060647089&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060647089&partnerID=8YFLogxK
U2 - 10.1109/ULTSYM.2018.8580078
DO - 10.1109/ULTSYM.2018.8580078
M3 - Conference contribution
AN - SCOPUS:85060647089
T3 - IEEE International Ultrasonics Symposium, IUS
BT - 2018 IEEE International Ultrasonics Symposium, IUS 2018
PB - IEEE Computer Society
T2 - 2018 IEEE International Ultrasonics Symposium, IUS 2018
Y2 - 22 October 2018 through 25 October 2018
ER -