TY - GEN
T1 - Internal bleeding detection algorithm based on determination of organ boundary by low-brightness set analysis
AU - Ito, Keiichiro
AU - Sugano, Shigeki
AU - Iwata, Hiroyasu
PY - 2012/12/1
Y1 - 2012/12/1
N2 - This paper proposes an organ boundary determination method for detecting internal bleeding. Focused assessment with sonography for trauma (FAST) is important for patients who are sent into shock by internal bleeding. However, the FAST has a low sensitivity, approximately 42.7 %, and delays of lifesaving treatment due to internal bleeding being missed have become a serious problem in emergency medical care. This study aims, therefore, to construct an automatic internal bleeding detection robotic system on the basis of ultrasound (US) image processing to improve the sensitivity. Internal bleeding has two key features: it is extracted from low-brightness areas in US images and accumulates between organs. We developed method for extracting low-brightness areas and determining algorithms of organ boundaries by low-brightness set analysis, and we detect internal bleeding by combining these two methods. Experimental results based on clinical US images of internal bleeding between Liver and Kidney showed that proposed algorithms had a sensitivity of 77.8% and specificity of 95.7%.
AB - This paper proposes an organ boundary determination method for detecting internal bleeding. Focused assessment with sonography for trauma (FAST) is important for patients who are sent into shock by internal bleeding. However, the FAST has a low sensitivity, approximately 42.7 %, and delays of lifesaving treatment due to internal bleeding being missed have become a serious problem in emergency medical care. This study aims, therefore, to construct an automatic internal bleeding detection robotic system on the basis of ultrasound (US) image processing to improve the sensitivity. Internal bleeding has two key features: it is extracted from low-brightness areas in US images and accumulates between organs. We developed method for extracting low-brightness areas and determining algorithms of organ boundaries by low-brightness set analysis, and we detect internal bleeding by combining these two methods. Experimental results based on clinical US images of internal bleeding between Liver and Kidney showed that proposed algorithms had a sensitivity of 77.8% and specificity of 95.7%.
KW - Emergency Medical Care
KW - Image processing
KW - Visual Feedback
KW - Wearable system
UR - http://www.scopus.com/inward/record.url?scp=84872298050&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84872298050&partnerID=8YFLogxK
U2 - 10.1109/IROS.2012.6385745
DO - 10.1109/IROS.2012.6385745
M3 - Conference contribution
AN - SCOPUS:84872298050
SN - 9781467317375
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 4131
EP - 4136
BT - 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012
T2 - 25th IEEE/RSJ International Conference on Robotics and Intelligent Systems, IROS 2012
Y2 - 7 October 2012 through 12 October 2012
ER -