TY - GEN
T1 - Joint probability discrimination between stationary tissue and blood velocity signals
AU - Schlaikjer, Malene
AU - Jensen, Jørgen Arendt
N1 - Copyright: 2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE
PY - 2001
Y1 - 2001
N2 - In CFM-mode the blood velocity estimates are overlaid onto the B-mode image. The velocity estimation gives non-zero velocity estimates in both the surrounding tissue and the vessels. A discrimination algorithm is needed to determine, which estimates represent blood flow and should be displayed. This study presents a new statistical discriminator. Investigation of the RF-signals reveals that features can be derived that distinguish the segments of the signal, which do an do not carry information on the blood flow. In this study 4 features, have been determined: (a) the energy content in the segments before and after echo-canceling, and (b) the amplitude variations between samples in consecutive RF-signals before and after echo-canceling. The statistical discriminator was obtained by computing the probability density functions (PDFs) for each feature through histogram analysis of data. The discrimination is performed by determining the joint probability of the features for the segment under investigation and choosing the segment type that is most likely. The method was tested on simulated data resembling RF-signals from the carotid artery.
AB - In CFM-mode the blood velocity estimates are overlaid onto the B-mode image. The velocity estimation gives non-zero velocity estimates in both the surrounding tissue and the vessels. A discrimination algorithm is needed to determine, which estimates represent blood flow and should be displayed. This study presents a new statistical discriminator. Investigation of the RF-signals reveals that features can be derived that distinguish the segments of the signal, which do an do not carry information on the blood flow. In this study 4 features, have been determined: (a) the energy content in the segments before and after echo-canceling, and (b) the amplitude variations between samples in consecutive RF-signals before and after echo-canceling. The statistical discriminator was obtained by computing the probability density functions (PDFs) for each feature through histogram analysis of data. The discrimination is performed by determining the joint probability of the features for the segment under investigation and choosing the segment type that is most likely. The method was tested on simulated data resembling RF-signals from the carotid artery.
U2 - 10.1109/ULTSYM.2001.991982
DO - 10.1109/ULTSYM.2001.991982
M3 - Article in proceedings
SN - 0-7803-7177-1
VL - 1-2
T3 - I E E E International Ultrasonics Symposium. Proceedings
SP - 1397
EP - 1400
BT - 2001 IEEE International Ultrasonic Symposium Proceedings
PB - IEEE
T2 - IEEE International Ultrasonic Symposium 2001
Y2 - 7 October 2001 through 10 October 2001
ER -