TY - GEN
T1 - Carotid artery B-mode ultrasound image segmentation based on morphology, geometry and gradient direction
AU - Sunarya, I. Made Gede
AU - Yuniarno, Eko Mulyanto
AU - Purnomo, Mauridhi Hery
AU - Sardjono, Tri Arief
AU - Sunu, Ismoyo
AU - Purnama, I. Ketut Eddy
N1 - Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2017
Y1 - 2017
N2 - Carotid Artery (CA) is one of the vital organs in the human body. CA features that can be used are position, size and volume. Position feature can used to determine the preliminary initialization of the tracking. Examination of the CA features can use Ultrasound. Ultrasound imaging can be operated dependently by an skilled operator, hence there could be some differences in the images result obtained by two or more different operators. This can affect the process of determining of CA. To reduce the level of subjectivity among operators, it can determine the position of the CA automatically. In this study, the proposed method is to segment CA in B-Mode Ultrasound Image based on morphology, geometry and gradient direction. This study consists of three steps, the data collection, preprocessing and artery segmentation. The data used in this study were taken directly by the researchers and taken from the Brno university's signal processing lab database. Each data set contains 100 carotid artery B-Mode ultrasound image. Artery is modeled using ellipse with center c, major axis a and minor axis b. The proposed method has a high value on each data set, 97% (data set 1), 73 % (data set 2), 87% (data set 3). This segmentation results will then be used in the process of tracking the CA.
AB - Carotid Artery (CA) is one of the vital organs in the human body. CA features that can be used are position, size and volume. Position feature can used to determine the preliminary initialization of the tracking. Examination of the CA features can use Ultrasound. Ultrasound imaging can be operated dependently by an skilled operator, hence there could be some differences in the images result obtained by two or more different operators. This can affect the process of determining of CA. To reduce the level of subjectivity among operators, it can determine the position of the CA automatically. In this study, the proposed method is to segment CA in B-Mode Ultrasound Image based on morphology, geometry and gradient direction. This study consists of three steps, the data collection, preprocessing and artery segmentation. The data used in this study were taken directly by the researchers and taken from the Brno university's signal processing lab database. Each data set contains 100 carotid artery B-Mode ultrasound image. Artery is modeled using ellipse with center c, major axis a and minor axis b. The proposed method has a high value on each data set, 97% (data set 1), 73 % (data set 2), 87% (data set 3). This segmentation results will then be used in the process of tracking the CA.
KW - Carotid artery
KW - Gradient direction
KW - Morphology
KW - Segmentation
KW - Ultrasound image
UR - http://www.scopus.com/inward/record.url?scp=85028551934&partnerID=8YFLogxK
U2 - 10.1117/12.2280617
DO - 10.1117/12.2280617
M3 - Conference contribution
AN - SCOPUS:85028551934
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Second International Workshop on Pattern Recognition
A2 - Chen, Guojian
A2 - Jiang, Xudong
A2 - Arai, Masayuki
PB - SPIE
T2 - 2nd International Workshop on Pattern Recognition, IWPR 2017
Y2 - 1 May 2017 through 3 May 2017
ER -