Vanessa Gonzalez-Duque

Ecole Centrale de Nantes | EC Nantes · Department of Computer Science and Mathematics

We present an accurate, fast and efficient method for segmentation and muscle mask propagation in 3D freehand ultrasound data, towards accurate volume quantification. A deep Siamese 3D Encoder-Decoder network that captures the evolution of the muscle appearance and shape for contiguous slices is deployed. We use it to propagate a reference mask ann...

We present an accurate, fast and efficient method for segmentation and muscle mask propagation in 3D freehand ultrasound data, towards accurate volume quantification. A deep Siamese 3D Encoder-Decoder network that captures the evolution of the muscle appearance and shape for contiguous slices is deployed. We uses it to propagate a reference mask an...

The manual segmentation of multiple organs in 3D ultra-sound (US) sequences and volumes towards their quantitative analysis is very expensive and time-consuming. Fully supervised segmentation methods still require the collection of large volumes of annotated data while unlabeled images are abundant. In this work, we propose a semi-automatic deep le...

The manual segmentation of multiple organs in 3D ultra-sound (US) sequences and volumes towards their quantitative analysis is very expensive and time-consuming. Fully supervised segmenta-tion methods still require the collection of large volumes of annotated data while unlabeled images are abundant. In this work, we propose a semi-automatic deep l...