TY - GEN
T1 - Enhanced Shear Wave Velocity Calculation in Glaucoma Patients using Adaptive Singular Value Filter and Deep Neural Network in Ultrasound Elastography
AU - Bui, Ngoc Thang
AU - Kazemi, Arash
AU - Chen, John
AU - Larson, Nicholas B.
AU - Sit, Arthur J
AU - Zhang, Xiaoming
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Objective: The purpose of this study was to develop an adaptive singular value decomposition filter (SVF) method for improving calculation of shear wave velocity (SWV) on two locations of cornea and sclera for patients with glaucoma. Methods: Three patients with glaucoma and three healthy controls were enrolled in this study. We employed two independents adaptive SVFs for two regions of interest (ROI) of cornea and sclera (SVF-ROI). The deep neural network (DNN) was used to select the high efficiency cutoff value for SVF-ROI of two ROIs of cornea and sclera for reducing the noise of B-mode imaging and SWV. Results: We observed a trend of improved SNR when considering SWV values using three methods (i.e., no filter, the SVF, and SVF-ROI) for both eyes at the sclera (13.9, 14.8, and 19.6, respectively) and cornea (4.32, 4.29, and 9.78, respectively). Conclusion: significant improvement in SNR of SWV were found between the eyes with glaucoma and healthy eyes. Significance: The SVF-ROI provides an innovative method to increase accuracy of the vibro-ultrasound technique for assessing patients with glaucoma.
AB - Objective: The purpose of this study was to develop an adaptive singular value decomposition filter (SVF) method for improving calculation of shear wave velocity (SWV) on two locations of cornea and sclera for patients with glaucoma. Methods: Three patients with glaucoma and three healthy controls were enrolled in this study. We employed two independents adaptive SVFs for two regions of interest (ROI) of cornea and sclera (SVF-ROI). The deep neural network (DNN) was used to select the high efficiency cutoff value for SVF-ROI of two ROIs of cornea and sclera for reducing the noise of B-mode imaging and SWV. Results: We observed a trend of improved SNR when considering SWV values using three methods (i.e., no filter, the SVF, and SVF-ROI) for both eyes at the sclera (13.9, 14.8, and 19.6, respectively) and cornea (4.32, 4.29, and 9.78, respectively). Conclusion: significant improvement in SNR of SWV were found between the eyes with glaucoma and healthy eyes. Significance: The SVF-ROI provides an innovative method to increase accuracy of the vibro-ultrasound technique for assessing patients with glaucoma.
KW - adaptive singular value filter
KW - deep neural network
KW - glaucoma
KW - shear wave velocity
UR - http://www.scopus.com/inward/record.url?scp=85178627551&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85178627551&partnerID=8YFLogxK
U2 - 10.1109/IUS51837.2023.10307106
DO - 10.1109/IUS51837.2023.10307106
M3 - Conference contribution
AN - SCOPUS:85178627551
T3 - IEEE International Ultrasonics Symposium, IUS
BT - IUS 2023 - IEEE International Ultrasonics Symposium, Proceedings
PB - IEEE Computer Society
T2 - 2023 IEEE International Ultrasonics Symposium, IUS 2023
Y2 - 3 September 2023 through 8 September 2023
ER -