Mathilde M. W. Wille

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We present a fast and robust supervised algorithm for labeling anatomical airway trees, based on geodesic distances in a geometric tree-space. Possible branch label configurations for a given tree are evaluated based on distances to a training set of labeled trees. In tree-space, the tree topology and geometry change continuously, giving a natural way to(More)
We propose a novel Computer-Aided Detection (CAD) system for pulmonary nodules using multi-view convolutional networks (ConvNets), for which discriminative features are automatically learnt from the training data. The network is fed with nodule candidates obtained by combining three candidate detectors specifically designed for solid, subsolid, and large(More)
Statistical analysis of anatomical trees is hard to perform due to differences in the topological structure of the trees. In this paper we define statistical properties of leaf-labeled anatomical trees with geometric edge attributes by considering the anatomical trees as points in the geometric space of leaf-labeled trees. This tree-space is a geodesic(More)
We present a novel descriptor for the characterization of pulmonary nodules in computed tomography (CT) images. The descriptor encodes information on nodule morphology and has scale-invariant and rotation-invariant properties. Information on nodule morphology is captured by sampling intensity profiles along circular patterns on spherical surfaces centered(More)
The introduction of lung cancer screening programs will produce an unprecedented amount of chest CT scans in the near future, which radiologists will have to read in order to decide on a patient follow-up strategy. According to the current guidelines, the workup of screen-detected nodules strongly relies on nodule size and nodule type. In this paper, we(More)
Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models. From the DLCST database, 1,152 nodules from 718 participants were included. Parsimonious(More)
To evaluate interobserver agreement and time-trend in chest CT assessment of emphysema, airways, and interstitial abnormalities in a lung cancer screening cohort. Visual assessment of baseline and fifth-year examination of 1990 participants was performed independently by two observers. Results were standardised by means of an electronic score sheet; kappa(More)
To study the effect of inspiration on airway dimensions measured in voluntary inspiration breath-hold examinations. 961 subjects with normal spirometry were selected from the Danish Lung Cancer Screening Trial. Subjects were examined annually for five years with low-dose CT. Automated software was utilized to segment lungs and airways, identify segmental(More)
RATIONALE As of April 2015, participants in the Danish Lung Cancer Screening Trial had been followed for at least 5 years since their last screening. OBJECTIVES Mortality, causes of death, and lung cancer findings are reported to explore the effect of computed tomography (CT) screening. METHODS A total of 4,104 participants aged 50-70 years at the time(More)
This paper introduces a graph construction method for multi-dimensional and multi-surface segmentation problems. Such problems can be solved by searching for the optimal separating surfaces given the space of graph columns defined by an initial coarse surface. Conventional straight graph columns are not well suited for surfaces with high curvature, we(More)