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IEEE Transactions on Medical Imaging
|
November 25, 2014
Bag-of-frequencies: a descriptor of pulmonary nodules in computed tomography images
Francesco Ciompi, Colin Jacobs, Ernst Th Scholten, et al.
Investigative Radiology
|
December 6, 2014
Solid, part-solid, or non-solid?: classification of pulmonary nodules in low-dose chest computed tomography by a computer-aided diagnosis system
Colin Jacobs, Eva M van Rikxoort, Ernst Th Scholten, et al.
European Radiology
|
April 26, 2017
Malignancy estimation of Lung-RADS criteria for subsolid nodules on CT: accuracy of low and high risk spectrum when using NLST nodules
Kaman Chung, Colin Jacobs, Ernst T Scholten, et al.
Plos One
|
February 14, 2018
Visual discrimination of screen-detected persistent from transient subsolid nodules: An observer study
Kaman Chung, Francesco Ciompi, Ernst T Scholten, et al.
IEEE Transactions on Artificial Intelligence
|
May 18, 2022
Automated COVID-19 Grading With Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison
Coen de Vente, Luuk H Boulogne, Kiran Vaidhya Venkadesh, et al.
European Radiology
|
July 15, 2025
Performance of a screening-trained DL model for pulmonary nodule malignancy estimation of incidental clinical nodules
Renate Dinnessen, Dré Peeters, Noa Antonissen, et al.
Plos One
|
December 12, 2017
Normalized emphysema scores on low dose CT: Validation as an imaging biomarker for mortality
Leticia Gallardo-Estrella, Esther Pompe, Pim A de Jong, et al.
Radiology
|
July 4, 2018
Classification of CT Pulmonary Opacities as Perifissural Nodules: Reader Variability
Anton Schreuder, Bram van Ginneken, Ernst T Scholten, et al.
Cancers
|
July 2, 2021
CT-Detected Subsolid Nodules: A Predictor of Lung Cancer Development at Another Location?
Anton Schreuder, Mathias Prokop, Ernst T Scholten, et al.
European Radiology
|
March 27, 2024
Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation
Dré Peeters, Natália Alves, Kiran V Venkadesh, et al.
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Showing results (41-50 of 93) with videos related to
Sort By:
Page
of 10
IEEE Transactions on Medical Imaging
|
November 25, 2014
Bag-of-frequencies: a descriptor of pulmonary nodules in computed tomography images
Francesco Ciompi, Colin Jacobs, Ernst Th Scholten, et al.
Investigative Radiology
|
December 6, 2014
Solid, part-solid, or non-solid?: classification of pulmonary nodules in low-dose chest computed tomography by a computer-aided diagnosis system
Colin Jacobs, Eva M van Rikxoort, Ernst Th Scholten, et al.
European Radiology
|
April 26, 2017
Malignancy estimation of Lung-RADS criteria for subsolid nodules on CT: accuracy of low and high risk spectrum when using NLST nodules
Kaman Chung, Colin Jacobs, Ernst T Scholten, et al.
Plos One
|
February 14, 2018
Visual discrimination of screen-detected persistent from transient subsolid nodules: An observer study
Kaman Chung, Francesco Ciompi, Ernst T Scholten, et al.
IEEE Transactions on Artificial Intelligence
|
May 18, 2022
Automated COVID-19 Grading With Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison
Coen de Vente, Luuk H Boulogne, Kiran Vaidhya Venkadesh, et al.
European Radiology
|
July 15, 2025
Performance of a screening-trained DL model for pulmonary nodule malignancy estimation of incidental clinical nodules
Renate Dinnessen, Dré Peeters, Noa Antonissen, et al.
Plos One
|
December 12, 2017
Normalized emphysema scores on low dose CT: Validation as an imaging biomarker for mortality
Leticia Gallardo-Estrella, Esther Pompe, Pim A de Jong, et al.
Radiology
|
July 4, 2018
Classification of CT Pulmonary Opacities as Perifissural Nodules: Reader Variability
Anton Schreuder, Bram van Ginneken, Ernst T Scholten, et al.
Cancers
|
July 2, 2021
CT-Detected Subsolid Nodules: A Predictor of Lung Cancer Development at Another Location?
Anton Schreuder, Mathias Prokop, Ernst T Scholten, et al.
European Radiology
|
March 27, 2024
Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation
Dré Peeters, Natália Alves, Kiran V Venkadesh, et al.
Page
of 10