Search Results - "Wille, Mathilde M. W"

Visual assessment of early emphysema and interstitial abnormalities on CT is useful in lung cancer risk analysis by Wille, Mathilde M. W., Thomsen, Laura H., Petersen, Jens, de Bruijne, Marleen, Dirksen, Asger, Pedersen, Jesper H., Shaker, Saher B.

“…Objectives Screening for lung cancer should be limited to a high-risk-population, and abnormalities in low-dose computed tomography (CT) screening images may…”
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Increased respiratory morbidity in individuals with interstitial lung abnormalities by Hoyer, Nils, Thomsen, Laura H, Wille, Mathilde M W, Wilcke, Torgny, Dirksen, Asger, Pedersen, Jesper H, Saghir, Zaigham, Ashraf, Haseem, Shaker, Saher B

“…Interstitial lung abnormalities (ILA) are common in participants of lung cancer screening trials and broad population-based cohorts. They are associated with…”
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Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT by Venkadesh, Kiran Vaidhya, Setio, Arnaud A A, Schreuder, Anton, Scholten, Ernst T, Chung, Kaman, W Wille, Mathilde M, Saghir, Zaigham, van Ginneken, Bram, Prokop, Mathias, Jacobs, Colin

“…Background Accurate estimation of the malignancy risk of pulmonary nodules at chest CT is crucial for optimizing management in lung cancer screening. Purpose…”
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Interstitial lung abnormalities are associated with increased mortality in smokers by Hoyer, Nils, Wille, Mathilde M.W., Thomsen, Laura H., Wilcke, Torgny, Dirksen, Asger, Pedersen, Jesper H., Saghir, Zaigham, Ashraf, Haseem, Shaker, Saher B.

“…The aim of this study was to investigate whether smokers with incidental findings of interstitial lung abnormalities have an increased mortality during…”
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Effect of inspiration on airway dimensions measured in maximal inspiration CT images of subjects without airflow limitation by Petersen, Jens, Wille, Mathilde M. W., Rakêt, Lars Lau, Feragen, Aasa, Pedersen, Jesper H., Nielsen, Mads, Dirksen, Asger, de Bruijne, Marleen

“…Objectives To study the effect of inspiration on airway dimensions measured in voluntary inspiration breath-hold examinations. Methods 961 subjects with normal…”
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Towards automatic pulmonary nodule management in lung cancer screening with deep learning by Ciompi, Francesco, Chung, Kaman, van Riel, Sarah J., Setio, Arnaud Arindra Adiyoso, Gerke, Paul K., Jacobs, Colin, Scholten, Ernst Th, Schaefer-Prokop, Cornelia, Wille, Mathilde M. W., Marchianò, Alfonso, Pastorino, Ugo, Prokop, Mathias, van Ginneken, Bram

“…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…”
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Results of the Randomized Danish Lung Cancer Screening Trial with Focus on High-Risk Profiling by Wille, Mathilde M W, Dirksen, Asger, Ashraf, Haseem, Saghir, Zaigham, Bach, Karen S, Brodersen, John, Clementsen, Paul F, Hansen, Hanne, Larsen, Klaus R, Mortensen, Jann, Rasmussen, Jakob F, Seersholm, Niels, Skov, Birgit G, Thomsen, Laura H, Tønnesen, Philip, Pedersen, Jesper H

“…As of April 2015, participants in the Danish Lung Cancer Screening Trial had been followed for at least 5 years since their last screening. Mortality, causes…”
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Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem by Tennakoon, Ruwan, Bortsova, Gerda, Orting, Silas, Gostar, Amirali K., Wille, Mathilde M. W., Saghir, Zaigham, Hoseinnezhad, Reza, de Bruijne, Marleen, Bab-Hadiashar, Alireza

“…Volumetric imaging is an essential diagnostic tool for medical practitioners. The use of popular techniques such as convolutional neural networks (CNN) for…”
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Bag-of-Frequencies: A Descriptor of Pulmonary Nodules in Computed Tomography Images by Ciompi, Francesco, Jacobs, Colin, Scholten, Ernst T., Wille, Mathilde M. W., de Jong, Pim A., Prokop, Mathias, van Ginneken, Bram

“…We present a novel descriptor for the characterization of pulmonary nodules in computed tomography (CT) images. The descriptor encodes information on nodule…”
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Computed Tomography-based Subclassification of Chronic Obstructive Pulmonary Disease by Dirksen, Asger, Wille, Mathilde M W

“…Computed tomography (CT) is an obvious modality for subclassification of COPD. Traditionally, the pulmonary involvement of chronic obstructive pulmonary…”
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Learning to Quantify Emphysema Extent: What Labels Do We Need? by Orting, Silas Nyboe, Petersen, Jens, Thomsen, Laura H., Wille, Mathilde M. W., de Bruijne, Marleen

“…Accurate assessment of pulmonary emphysema is crucial to assess disease severity and subtype, to monitor disease progression, and to predict lung cancer risk…”
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Detecting emphysema with multiple instance learning by Orting, Silas Nyboe, Petersen, Jens, Thomsen, Laura H., Wille, Mathilde M W, de Bruijne, Marleen

“…Emphysema is part of chronic obstructive pulmonary disease, a leading cause of mortality worldwide. Visual assessment of emphysema presence is useful for…”
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A hierarchical scheme for geodesic anatomical labeling of airway trees by Feragen, Aasa, Petersen, Jens, Owen, Megan, Lo, Pechin, Thomsen, Laura H, Wille, Mathilde M W, Dirksen, Asger, de Bruijne, Marleen

“…We present a fast and robust supervised algorithm for labeling anatomical airway trees, based on geodesic distances in a geometric tree-space. Possible branch…”
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Towards automatic pulmonary nodule management in lung cancer screening with deep learning by Ciompi, Francesco, Chung, Kaman, van Riel, Sarah J, Setio, Arnaud Arindra Adiyoso, Gerke, Paul K, Jacobs, Colin, Scholten, Ernst Th, Schaefer-Prokop, Cornelia, Wille, Mathilde M. W, Marchiano, Alfonso, Pastorino, Ugo, Prokop, Mathias, van Ginneken, Bram

“…Sci. Rep. 7, 46479; (2017) The introduction of lung cancer screening programs will produce an unprecedented amount of chest CT scans in the near future, which…”
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Tree-space statistics and approximations for large-scale analysis of anatomical trees by Feragen, Aasa, Owen, Megan, Petersen, Jens, Wille, Mathilde M W, Thomsen, Laura H, Dirksen, Asger, de Bruijne, Marleen

“…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…”
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Learning to quantify emphysema extent: What labels do we need? by Ørting, Silas Nyboe, Petersen, Jens, Thomsen, Laura H, Wille, Mathilde M. W, de Bruijne, Marleen

“…Accurate assessment of pulmonary emphysema is crucial to assess disease severity and subtype, to monitor disease progression and to predict lung cancer risk…”
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Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans by Ørting, Silas Nyboe, Petersen, Jens, Cheplygina, Veronika, Thomsen, Laura H, Wille, Mathilde M W, de Bruijne, Marleen

“…Supervised feature learning using convolutional neural networks (CNNs) can provide concise and disease relevant representations of medical images. However,…”
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