89 citations · 144 across the 10 of their papers we have counts for
10 papers
Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks
Raghavendra Selvan, Thomas Kipf, Max Welling +4
Graph refinement, or the task of obtaining subgraphs of interest from over-complete graphs, can have many varied applications. In this work, we extract trees or collection of sub-t…
Extracting Tree-structures in CT data by Tracking Multiple Statistically Ranked Hypotheses
Raghavendra Selvan, Jens Petersen, Jesper H Pedersen +1
In this work, we adapt a method based on multiple hypothesis tracking (MHT) that has been shown to give state-of-the-art vessel segmentation results in interactive settings, for th…
Extraction of Airways using Graph Neural Networks
Raghavendra Selvan, Thomas Kipf, Max Welling +3
We present extraction of tree structures, such as airways, from image data as a graph refinement task. To this end, we propose a graph auto-encoder model that uses an encoder based…
Mean Field Network based Graph Refinement with application to Airway Tree Extraction
Raghavendra Selvan, Max Welling, Jesper H. Pedersen +2
We present tree extraction in 3D images as a graph refinement task, of obtaining a subgraph from an over-complete input graph. To this end, we formulate an approximate Bayesian inf…
Extraction of Airways with Probabilistic State-space Models and Bayesian Smoothing
Raghavendra Selvan, Jens Petersen, Jesper H. Pedersen +1
Segmenting tree structures is common in several image processing applications. In medical image analysis, reliable segmentations of airways, vessels, neurons and other tree structu…
Classification of COPD with Multiple Instance Learning
Veronika Cheplygina, Lauge Sørensen, David M. J. Tax +3
Chronic obstructive pulmonary disease (COPD) is a lung disease where early detection benefits the survival rate. COPD can be quantified by classifying patches of computed tomograph…