10 citations · 23 across the 5 of their papers we have counts for
5 papers
Efficient Deep Model-Based Optoacoustic Image Reconstruction
Christoph Dehner, Guillaume Zahnd
Clinical adoption of multispectral optoacoustic tomography necessitates improvements of the image quality available in real-time, as well as a reduction in the scanner financial co…
DeepMB: Deep neural network for real-time optoacoustic image reconstruction with adjustable speed of sound
Christoph Dehner, Guillaume Zahnd, Vasilis Ntziachristos +1
Multispectral optoacoustic tomography (MSOT) is a high-resolution functional imaging modality that can non-invasively access a broad range of pathophysiological phenomena by quanti…
Carotid artery wall segmentation in ultrasound image sequences using a deep convolutional neural network
Nolann Lainé, Guillaume Zahnd, Herv é Liebgott +1
The objective of this study is the segmentation of the intima-media complex of the common carotid artery, on longitudinal ultrasound images, to measure its thickness. We propose a…
Adaptive Image-Feature Learning for Disease Classification Using Inductive Graph Networks
Hendrik Burwinkel, Anees Kazi, Gerome Vivar +4
Recently, Geometric Deep Learning (GDL) has been introduced as a novel and versatile framework for computer-aided disease classification. GDL uses patient meta-information such as…
Dynamic Block Matching to assess the longitudinal component of the dense motion field of the carotid artery wall in B-mode ultrasound sequences -- Association with coronary artery disease
Guillaume Zahnd, Kozue Saito, Kazuyuki Nagatsuka +2
Purpose: The motion of the common carotid artery tissue layers along the vessel axis during the cardiac cycle, observed in ultrasound imaging, is associated with the presence of es…