Pierre-Alexandre Poletti

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This paper describes the methodology used to create a multimedia collection of cases with interstitial lung diseases (ILDs) at the University Hospitals of Geneva. The dataset contains high-resolution computed tomography (HRCT) image series with three-dimensional annotated regions of pathological lung tissue along with clinical parameters from patients with(More)
We describe a texture classification system that identifies lung tissue patterns from high-resolution computed tomography (HRCT) images of patients affected with interstitial lung diseases (ILD). This pattern recognition task is part of an image-based diagnostic aid system for ILDs. Five lung tissue patterns (healthy, emphysema, ground glass, fibrosis and(More)
We propose near-affine-invariant texture descriptors derived from isotropic wavelet frames for the characterization of lung tissue patterns in high-resolution computed tomography (HRCT) imaging. Affine invariance is desirable to enable learning of nondeterministic textures without a priori localizations, orientations, or sizes. When combined with(More)
BACKGROUND In the past decade the issue of patient mobility has emerged on the European health policy agenda. Although the volume of patients crossing borders to obtain healthcare is low, it is increasing continuously and, due to its legal, financial and medical implications, has generated considerable interest among health policy and other decision makers.(More)
OBJECTIVE We investigate the influence of the clinical context of high-resolution computed tomography (HRCT) images of the chest on tissue classification. METHODS AND MATERIALS 2D regions of interest in HRCT axial slices from patients affected with an interstitial lung disease are automatically classified into five classes of lung tissue. Relevance of the(More)
In this paper, we compare five common classifier families in their ability to categorize six lung tissue patterns in high-resolution computed tomography (HRCT) images of patients affected with interstitial lung diseases (ILD) and with healthy tissue. The evaluated classifiers are naive Bayes, k-nearest neighbor, J48 decision trees, multilayer perceptron,(More)
BACKGROUND Multislice CT (MSCT) combined with D-dimer measurement can safely exclude pulmonary embolism in patients with a low or intermediate clinical probability of this disease. We compared this combination with a strategy in which both a negative venous ultrasonography of the leg and MSCT were needed to exclude pulmonary embolism. METHODS We included(More)
PURPOSE Clinical workflows and user interfaces of image-based computer-aided diagnosis (CAD) for interstitial lung diseases in high-resolution computed tomography are introduced and discussed. METHODS Three use cases are implemented to assist students, radiologists, and physicians in the diagnosis workup of interstitial lung diseases. RESULTS In a first(More)
We propose rotation–covariant texture analysis of 4D dual– energy computed tomography (DECT) as a diagnosis aid tool for acute pulmonary embolism in emergency radiology. The cornerstone of the proposed approach is to align 3D Riesz directional filters along bronchovascular structures to enable rotation–covariant comparisons of the parenchymal texture. The(More)