TY - GEN
T1 - Automated assessment of small bowel motility function based on feature points tracking
AU - Otsuki, Kazuki
AU - Furukawa, Akira
AU - Kanasaki, Shuzo
AU - Iwamoto, Yutaro
AU - Tateyama, Tomoko
AU - Chen, Yen Wei
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - In this paper, we propose an automated method for assessing small bowel contraction movement with Cine-MRI based on automatic feature points tracking. The proposed method comprises two steps. First, in the initial frame, the user selects two arbitrary points on the boundary of the small bowel. The distance between the two points represents the size of the small bowl. Second, each of the two points is automatically tracked by the use of Kanade-Lucas-Tomasi (KLT) tracker method in the temporal sequence images. The contraction movement of the small intestine can be automatically analyzed by tracking these two points. Compared with the conventional method based on small bowel segmentation, The KLT-tracker method allows us to analyze the small intestinal contraction movement faster and establish a more objective analysis method.
AB - In this paper, we propose an automated method for assessing small bowel contraction movement with Cine-MRI based on automatic feature points tracking. The proposed method comprises two steps. First, in the initial frame, the user selects two arbitrary points on the boundary of the small bowel. The distance between the two points represents the size of the small bowl. Second, each of the two points is automatically tracked by the use of Kanade-Lucas-Tomasi (KLT) tracker method in the temporal sequence images. The contraction movement of the small intestine can be automatically analyzed by tracking these two points. Compared with the conventional method based on small bowel segmentation, The KLT-tracker method allows us to analyze the small intestinal contraction movement faster and establish a more objective analysis method.
UR - http://www.scopus.com/inward/record.url?scp=85064908387&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064908387&partnerID=8YFLogxK
U2 - 10.1109/FSKD.2018.8687193
DO - 10.1109/FSKD.2018.8687193
M3 - Conference contribution
AN - SCOPUS:85064908387
T3 - ICNC-FSKD 2018 - 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery
SP - 437
EP - 440
BT - ICNC-FSKD 2018 - 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery
A2 - Xiao, Zheng
A2 - Wang, Lipo
A2 - Xiao, Guoqing
A2 - Ning, Xiong
A2 - Li, Kenli
A2 - Li, Maozhen
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2018
Y2 - 28 July 2018 through 30 July 2018
ER -