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of 60
pro vyhledávání: '"Setio, Arnaud A. A."'
Autor:
Gündel, Sebastian, Setio, Arnaud A. A., Ghesu, Florin C., Grbic, Sasa, Georgescu, Bogdan, Maier, Andreas, Comaniciu, Dorin
Chest radiography is the most common radiographic examination performed in daily clinical practice for the detection of various heart and lung abnormalities. The large amount of data to be read and reported, with more than 100 studies per day for a s
Externí odkaz:
http://arxiv.org/abs/2104.05261
Autor:
Guendel, Sebastian, Setio, Arnaud Arindra Adiyoso, Grbic, Sasa, Maier, Andreas, Comaniciu, Dorin
Chest X-ray (CXR) is the most common examination for fast detection of pulmonary abnormalities. Recently, automated algorithms have been developed to classify multiple diseases and abnormalities in CXR scans. However, because of the limited availabil
Externí odkaz:
http://arxiv.org/abs/2008.02030
Autor:
Liu, Siqi, Setio, Arnaud Arindra Adiyoso, Ghesu, Florin C., Gibson, Eli, Grbic, Sasa, Georgescu, Bogdan, Comaniciu, Dorin
Detecting malignant pulmonary nodules at an early stage can allow medical interventions which may increase the survival rate of lung cancer patients. Using computer vision techniques to detect nodules can improve the sensitivity and the speed of inte
Externí odkaz:
http://arxiv.org/abs/2003.03824
Autor:
Yang, Jie, Liu, Siqi, Grbic, Sasa, Setio, Arnaud Arindra Adiyoso, Xu, Zhoubing, Gibson, Eli, Chabin, Guillaume, Georgescu, Bogdan, Laine, Andrew F., Comaniciu, Dorin
Though large-scale datasets are essential for training deep learning systems, it is expensive to scale up the collection of medical imaging datasets. Synthesizing the objects of interests, such as lung nodules, in medical images based on the distribu
Externí odkaz:
http://arxiv.org/abs/1812.11204
Autor:
Liu, Siqi, Gibson, Eli, Grbic, Sasa, Xu, Zhoubing, Setio, Arnaud Arindra Adiyoso, Yang, Jie, Georgescu, Bogdan, Comaniciu, Dorin
The performance of medical image analysis systems is constrained by the quantity of high-quality image annotations. Such systems require data to be annotated by experts with years of training, especially when diagnostic decisions are involved. Such d
Externí odkaz:
http://arxiv.org/abs/1812.01737
Autor:
Litjens, Geert, Kooi, Thijs, Bejnordi, Babak Ehteshami, Setio, Arnaud Arindra Adiyoso, Ciompi, Francesco, Ghafoorian, Mohsen, van der Laak, Jeroen A. W. M., van Ginneken, Bram, Sánchez, Clara I.
Publikováno v:
Med Image Anal. (2017) 42:60-88
Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300
Externí odkaz:
http://arxiv.org/abs/1702.05747
Autor:
Setio, Arnaud Arindra Adiyoso, Traverso, Alberto, de Bel, Thomas, Berens, Moira S. N., Bogaard, Cas van den, Cerello, Piergiorgio, Chen, Hao, Dou, Qi, Fantacci, Maria Evelina, Geurts, Bram, van der Gugten, Robbert, Heng, Pheng Ann, Jansen, Bart, de Kaste, Michael M. J., Kotov, Valentin, Lin, Jack Yu-Hung, Manders, Jeroen T. M. C., Sónora-Mengana, Alexander, García-Naranjo, Juan Carlos, Papavasileiou, Evgenia, Prokop, Mathias, Saletta, Marco, Schaefer-Prokop, Cornelia M, Scholten, Ernst T., Scholten, Luuk, Snoeren, Miranda M., Torres, Ernesto Lopez, Vandemeulebroucke, Jef, Walasek, Nicole, Zuidhof, Guido C. A., van Ginneken, Bram, Jacobs, Colin
Automatic detection of pulmonary nodules in thoracic computed tomography (CT) scans has been an active area of research for the last two decades. However, there have only been few studies that provide a comparative performance evaluation of different
Externí odkaz:
http://arxiv.org/abs/1612.08012
Autor:
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
Publikováno v:
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 radiologists will have to read in order to decide on a patient follow-up strategy. According to the current guidelines
Externí odkaz:
http://arxiv.org/abs/1610.09157
Akademický článek
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Autor:
Setio, Arnaud Arindra Adiyoso, Traverso, Alberto, de Bel, Thomas, Berens, Moira S.N., Bogaard, Cas van den, Cerello, Piergiorgio, Chen, Hao, Dou, Qi, Fantacci, Maria Evelina, Geurts, Bram, Gugten, Robbert van der, Heng, Pheng Ann, Jansen, Bart, de Kaste, Michael M.J., Kotov, Valentin, Lin, Jack Yu-Hung, Manders, Jeroen T.M.C., Sóñora-Mengana, Alexander, García-Naranjo, Juan Carlos, Papavasileiou, Evgenia, Prokop, Mathias, Saletta, Marco, Schaefer-Prokop, Cornelia M, Scholten, Ernst T., Scholten, Luuk, Snoeren, Miranda M., Torres, Ernesto Lopez, Vandemeulebroucke, Jef, Walasek, Nicole, Zuidhof, Guido C.A., Ginneken, Bram van, Jacobs, Colin
Publikováno v:
In Medical Image Analysis December 2017 42:1-13