Christian Payer

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We explore the applicability of deep convolutional neural networks (CNNs) for multiple landmark localization in medical image data. Exploiting the idea of regressing heatmaps for individual landmark locations, we investigate several fully convolutional 2D and 3D CNN architectures by training them in an end-to-end manner. We further propose a novel(More)
Automated computer-aided analysis of lung vessels has shown to yield promising results for non-invasive diagnosis of lung diseases. To detect vascular changes which affect pulmonary arteries and veins differently, both compartments need to be identified. We present a novel, fully automatic method that separates arteries and veins in thoracic computed(More)
Biological age (BA) estimation from radiologic data is an important topic in clinical medicine, e.g. in determining endocrinological diseases or planning paediatric orthopaedic surgeries, while in legal medicine it is employed to approximate chronological age. In this work, we propose the use of deep convolutional neural networks (DCNN) for automatic BA(More)
Automated computer-aided analysis of lung vessels has shown to yield promising results for non-invasive diagnosis of lung diseases. In order to detect vascular changes affecting arteries and veins differently, an algorithm capable of identifying these two compartments is needed. We propose a fully automatic algorithm that separates arteries and veins in(More)
Modern deep learning methods achieve state-ofthe-art results in many computer vision tasks. While these methods perform well when trained on large datasets, deep learning methods suffer from overfitting and lack of generalization given smaller datasets. Especially in medical image analysis, acquisition of both imaging data and corresponding ground-truth(More)
Age estimation from radiologic data is an important topic in forensic medicine to assess chronological age or to discriminate minors from adults, e.g. asylum seekers lacking valid identification documents. In this work we propose automatic multi-factorial age estimation methods based on MRI data to extend the maximal age range from 19 years, as commonly(More)
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