TY - GEN
T1 - Automatic detection of cotton balls during brain surgery
T2 - Medical Imaging 2021: Ultrasonic Imaging and Tomography
AU - Mahapatra, Smruti
AU - Balamurugan, Manish
AU - Chung, Kathryn
AU - Kuppoor, Venkat
AU - Curry, Eli
AU - Aghabaglau, Fariba
AU - Kaovasia, Tarana Parvez
AU - Acord, Molly
AU - Ainechi, Ana
AU - Kim, Jeong Hun
AU - Tshey, Yohannes
AU - Ghinda, Christina Diana
AU - Son, Jennifer K.
AU - Pustavoitau, Aliaksei
AU - Tyler, Betty
AU - Robinson, Shenandoah D.
AU - Theodore, Nicholas
AU - Brem, Henry
AU - Huang, Judy
AU - Manbachi, Amir
N1 - Publisher Copyright:
© 2021 SPIE
PY - 2021
Y1 - 2021
N2 - Cotton balls are a versatile and efficient tool commonly used in neurosurgical procedures to absorb fluids and manipulate delicate tissues. However, the use of cotton balls is accompanied by the risk of accidental retention in the brain after surgery. Retained cotton balls can lead to dangerous immune responses and potential complications, such as adhesions and textilomas. In a previous study, we showed that ultrasound can be safely used to detect cotton balls in the operating area due to the distinct acoustic properties of cotton compared with the acoustic properties of surrounding tissue. In this study, we enhance the experimental setup using a 3D-printed custom depth box and a Butterfly IQ handheld ultrasound probe. Cotton balls were placed in variety of positions to evaluate size and depth detectability limits. Recorded images were then analyzed using a novel algorithm that implements recently released YOLOv4, a state-of-the-art, real-time object recognition system. As per the radiologists’ opinion, the algorithm was able to detect the cotton ball correctly 61% of the time, at approximately 32 FPS. The algorithm could accurately detect cotton balls up to 5mm in diameter, which corresponds to the size of surgical balls used by neurosurgeons, making the algorithm a promising candidate for regular intraoperative use.
AB - Cotton balls are a versatile and efficient tool commonly used in neurosurgical procedures to absorb fluids and manipulate delicate tissues. However, the use of cotton balls is accompanied by the risk of accidental retention in the brain after surgery. Retained cotton balls can lead to dangerous immune responses and potential complications, such as adhesions and textilomas. In a previous study, we showed that ultrasound can be safely used to detect cotton balls in the operating area due to the distinct acoustic properties of cotton compared with the acoustic properties of surrounding tissue. In this study, we enhance the experimental setup using a 3D-printed custom depth box and a Butterfly IQ handheld ultrasound probe. Cotton balls were placed in variety of positions to evaluate size and depth detectability limits. Recorded images were then analyzed using a novel algorithm that implements recently released YOLOv4, a state-of-the-art, real-time object recognition system. As per the radiologists’ opinion, the algorithm was able to detect the cotton ball correctly 61% of the time, at approximately 32 FPS. The algorithm could accurately detect cotton balls up to 5mm in diameter, which corresponds to the size of surgical balls used by neurosurgeons, making the algorithm a promising candidate for regular intraoperative use.
KW - Deep learning
KW - Neuroimaging
KW - Object detection
KW - Recognition system
KW - Retained foreign object
KW - Ultrasound
UR - http://www.scopus.com/inward/record.url?scp=85103442982&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85103442982&partnerID=8YFLogxK
U2 - 10.1117/12.2580887
DO - 10.1117/12.2580887
M3 - Conference contribution
C2 - 35233128
AN - SCOPUS:85103442982
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2021
A2 - Byram, Brett C.
A2 - Ruiter, Nicole V.
PB - SPIE
Y2 - 15 February 2021 through 19 February 2021
ER -