Catheter detection in 3D ultrasound by CNN

Hongxu Yang, Caifeng Shan, Alexander F. Kolen, Peter de With

Onderzoeksoutput: Bijdrage aan congresOtherAcademic


In this paper, we propose a catheter detection method based on convolutional neural networks (CNNs) in 3D US. Voxels in US images are classified as catheter (or not) using triplanarbased CNNs. Our proposed CNN employs two-stage training with weighted loss function, which can cope with highly imbalanced training data and improves classification accuracy. Based on classified volumes, the catheters are localized with an average position error of smaller than 3 voxels in the examined datasets, indicating that catheters are always detected
in noisy and low-resolution images.
Originele taal-2Engels
Aantal pagina's2
StatusGepubliceerd - 2018
EvenementThe Netherlands Conference on Computer Vision (NCCV 2018) -
Duur: 26 sep. 201827 sep. 2018


CongresThe Netherlands Conference on Computer Vision (NCCV 2018)
Verkorte titelNCCV 2018


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