08.12.2020The Menze group publishes DeepVesselNet, a deep learning approach to perform vessel segmentation, centerline prediction, and bifurcation detection tasks

DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes

See Tetteh et al, Front. Neurosci.

The code can be found on GitHub: Tetteh, 2019a

A ready-to-use implementation is available as companion material to the publication “Machine learning analysis of whole mouse brain vasculature”Todorov et al., 2020

Fig. 1 Tetteh 2020 — Fig.1: An overview of the three main tasks tackled in this paper. © 2020 The Author(s)

Back to news overview

Unterseiten

Support of applicants for the SNSF Professorial Fellowship / SNSF Starting Grant in the field of "Quantitative Biomedicine"
The Krauthammer Group Develops Explainable Deep Learning Model for Predicting Disease Activity in Joint Disorders
The Krauthammer group and collaborators develop advanced AI model to predict disease risk from multimodal data
In collaboration, the Joller group and the Krauthammer group reveal the regulatory role of tissue-specific Tregs in autoimmune diseases

Department of Quantitative Biomedicine

Quicklinks und Sprachwechsel

Main navigation

08.12.2020The Menze group publishes DeepVesselNet, a deep learning approach to perform vessel segmentation, centerline prediction, and bifurcation detection tasks

DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes

Unterseiten