Zobrazeno 1 - 10
of 983
pro vyhledávání: '"Automated lung segmentation"'
Autor:
Conrad, Alice Marguerite1 (AUTHOR), Zimmermann, Julia1 (AUTHOR), Mohr, David1 (AUTHOR), Froelich, Matthias F.2 (AUTHOR), Hertel, Alexander2 (AUTHOR), Rathmann, Nils2 (AUTHOR), Boesing, Christoph1 (AUTHOR), Thiel, Manfred1 (AUTHOR), Schoenberg, Stefan O.2 (AUTHOR), Krebs, Joerg1 (AUTHOR), Luecke, Thomas1 (AUTHOR), Rocco, Patricia R. M.3 (AUTHOR), Otto, Matthias1 (AUTHOR) matthias.otto@umm.de
Publikováno v:
Intensive Care Medicine Experimental. 11/2/2024, Vol. 12 Issue 1, p1-10. 10p.
Autor:
Alice Marguerite Conrad, Julia Zimmermann, David Mohr, Matthias F. Froelich, Alexander Hertel, Nils Rathmann, Christoph Boesing, Manfred Thiel, Stefan O. Schoenberg, Joerg Krebs, Thomas Luecke, Patricia R. M. Rocco, Matthias Otto
Publikováno v:
Intensive Care Medicine Experimental, Vol 12, Iss 1, Pp 1-10 (2024)
Abstract Background Quantification of pulmonary edema in patients with acute respiratory distress syndrome (ARDS) by chest computed tomography (CT) scan has not been validated in routine diagnostics due to its complexity and time-consuming nature. Th
Externí odkaz:
https://doaj.org/article/f645d7f055ca4edebc38aeb565cada46
Akademický článek
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Akademický článek
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Autor:
Friedemann G. Ringwald, Lena Wucherpfennig, Niclas Hagen, Jonas Mücke, Sebastian Kaletta, Monika Eichinger, Mirjam Stahl, Simon M. F. Triphan, Patricia Leutz-Schmidt, Sonja Gestewitz, Simon Y. Graeber, Hans-Ulrich Kauczor, Abdulsattar Alrajab, Jens-Peter Schenk, Olaf Sommerburg, Marcus A. Mall, Petra Knaup, Mark O. Wielpütz, Urs Eisenmann
Publikováno v:
Frontiers in Medicine, Vol 11 (2024)
IntroductionSegmentation of lung structures in medical imaging is crucial for the application of automated post-processing steps on lung diseases like cystic fibrosis (CF). Recently, machine learning methods, particularly neural networks, have demons
Externí odkaz:
https://doaj.org/article/c357ed5510a04bf597f2f82ce4f81936
Autor:
Gholamiankhah, Faeze, Mostafapour, Samaneh, Goushbolagh, Nouraddin Abdi, Shojaerazavi, Seyedjafar, Layegh, Parvaneh, Tabatabaei, Seyyed Mohammad, Arabi, Hossein
Automated semantic image segmentation is an essential step in quantitative image analysis and disease diagnosis. This study investigates the performance of a deep learning-based model for lung segmentation from CT images for normal and COVID-19 patie
Externí odkaz:
http://arxiv.org/abs/2104.02042
Autor:
Gholamiankhah, Faeze1, Mostafapour, Samaneh2, Goushbolagh, Nouraddin Abdi1, Shojaerazavi, Seyedjafar3, Layegh, Parvaneh4, Tabatabaei, Seyyed Mohammad5,6, Arabi, Hossein7 hossein.arabi@unige.ch
Publikováno v:
Iranian Journal of Medical Sciences. Sep2022, Vol. 47 Issue 5, p440-449. 10p.
Publikováno v:
In Biocybernetics and Biomedical Engineering July-September 2020 40(3):1314-1327
Autor:
Faeze Gholamiankhah, Samaneh Mostafapour, Nouraddin Abdi Goushbolagh, Seyedjafar Shojaerazavi, Parvaneh Layegh, Seyyed Mohammad Tabatabaei, Hossein Arabi
Publikováno v:
Iranian Journal of Medical Sciences, Vol 47, Iss 5, Pp 440-449 (2022)
Background: Automated image segmentation is an essential step in quantitative image analysis. This study assesses the performance of a deep learning-based model for lung segmentation from computed tomography (CT) images of normal and COVID-19 patient
Externí odkaz:
https://doaj.org/article/9f3900036b824bdf847798dd15d43c9b
Publikováno v:
In Computers in Biology and Medicine 1 December 2017 91:168-180