U-Net-based deep convolutional neural network for detection of superparamagnetic drug-eluting particles used for liver chemoembolization
NING LI1,2, Cyril Tous1,2, Phillip Fei1,2, Ivan P Dimov1,2, Simon Lessard1,2, Urs O. Häfeli3, Sylvain Martel4, An Tang1,2, and Gilles Soulez1,2
1Centre de recherche du Centre hospitalier de l’Université de Montréal (CRCHUM), Montreal, QC, Canada, 2Université de Montréal, Montreal, QC, Canada, 3University of British Columbia, Vancouver, BC, Canada, 4Polytechnique Montréal, Montreal, QC, Canada
Magnetic steering of superparamagnetic drug-eluting particles (SMDEPs) loaded with anti-tumor drugs across hepatic arteries is a promising technique to perform segmental liver embolization for patients with hepatocellular carcinomas (HCCs). These aggregates (20 ± 6 SMDEPs) are sequentially released with a specially designed injector through a catheter in the proper hepatic artery of a swine placed in an MRI. Manual segmentation was previously done to localize and count the particles (volume of the artifact) in each lobe. We propose to train a U-net over this pre-existing database. Dice similarity coefficient, accuracy, and precision were respectively 99.1%, 98.3%, and 84.6%.
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