Catheter detection in 3D ultrasound by CNN

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

Onderzoeksoutput: Bijdrage aan congresOtherAcademic

Samenvatting

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 2018 -
Duur: 26 sep 201827 sep 2018

Congres

CongresThe Netherlands Conference on Computer Vision 2018
Verkorte titelNCCV18
Periode26/09/1827/09/18

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  • Citeer dit

    Yang, H., Shan, C., Kolen, A. F., & de With, P. (2018). Catheter detection in 3D ultrasound by CNN. The Netherlands Conference on Computer Vision 2018, .