Zobrazeno 1 - 10
of 314
pro vyhledávání: '"Adrien, Depeursinge"'
Autor:
Sacha Bors, Daniel Abler, Matthieu Dietz, Vincent Andrearczyk, Julien Fageot, Marie Nicod-Lalonde, Niklaus Schaefer, Robert DeKemp, Christel H. Kamani, John O. Prior, Adrien Depeursinge
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Assessing the individual risk of Major Adverse Cardiac Events (MACE) is of major importance as cardiovascular diseases remain the leading cause of death worldwide. Quantitative Myocardial Perfusion Imaging (MPI) parameters such as stress Myo
Externí odkaz:
https://doaj.org/article/04d8552567144e6b9f4b562be9a2f82f
Autor:
Jakub Mlynář, Adrien Depeursinge, John O. Prior, Roger Schaer, Alexandre Martroye de Joly, Florian Evéquoz
Publikováno v:
Frontiers in Communication, Vol 8 (2024)
Technologies based on “artificial intelligence” (AI) are transforming every part of our society, including healthcare and medical institutions. An example of this trend is the novel field in oncology and radiology called radiomics, which is the e
Externí odkaz:
https://doaj.org/article/05d10f15d0ea4b69925f4bd3fe68c761
Autor:
Daniel Abler, Roger Schaer, Valentin Oreiller, Himanshu Verma, Julien Reichenbach, Orfeas Aidonopoulos, Florian Evéquoz, Mario Jreige, John O. Prior, Adrien Depeursinge
Publikováno v:
European Radiology Experimental, Vol 7, Iss 1, Pp 1-13 (2023)
Abstract Background Radiomics, the field of image-based computational medical biomarker research, has experienced rapid growth over the past decade due to its potential to revolutionize the development of personalized decision support models. However
Externí odkaz:
https://doaj.org/article/9359553e1fe548328f030500f1f75194
Autor:
Daphné Faist, Mario Jreige, Valentin Oreiller, Marie Nicod Lalonde, Niklaus Schaefer, Adrien Depeursinge, John O. Prior
Publikováno v:
European Journal of Hybrid Imaging, Vol 6, Iss 1, Pp 1-9 (2022)
Abstract Background Quality and reproducibility of radiomics studies are essential requirements for the standardisation of radiomics models. As recent data-driven respiratory gating (DDG) [18F]-FDG has shown superior diagnostic performance in lung ca
Externí odkaz:
https://doaj.org/article/e9b72338bc5e4902b465c9defa8117ca
Autor:
Pierre Fontaine, Vincent Andrearczyk, Valentin Oreiller, Daniel Abler, Joel Castelli, Oscar Acosta, Renaud De Crevoisier, Martin Vallières, Mario Jreige, John O. Prior, Adrien Depeursinge
Publikováno v:
Clinical and Translational Radiation Oncology, Vol 33, Iss , Pp 153-158 (2022)
A vast majority of studies in the radiomics field are based on contours originating from radiotherapy planning. This kind of delineation (e.g. Gross Tumor Volume, GTV) is often larger than the true tumoral volume, sometimes including parts of other o
Externí odkaz:
https://doaj.org/article/9725dd9e1fed425185c7e9ed0ca0aa43
Autor:
Kyriakos Flouris, Oscar Jimenez-del-Toro, Christoph Aberle, Michael Bach, Roger Schaer, Markus M. Obmann, Bram Stieltjes, Henning Müller, Adrien Depeursinge, Ender Konukoglu
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-11 (2022)
Abstract Medical imaging quantitative features had once disputable usefulness in clinical studies. Nowadays, advancements in analysis techniques, for instance through machine learning, have enabled quantitative features to be progressively useful in
Externí odkaz:
https://doaj.org/article/e8f4905eaa4d4d5d8a6895e1a33be895
Publikováno v:
Informatics in Medicine Unlocked, Vol 43, Iss , Pp 101403- (2023)
The locality and spatial field of view of image operators have played a major role in image analysis, from hand-crafted to deep learning methods. In Convolutional Neural Networks (CNNs), the field of view is traditionally set to very small values (e.
Externí odkaz:
https://doaj.org/article/e22c911486dc43c4b640e9d229d733c1
Autor:
Federico Spagnolo, Adrien Depeursinge, Sabine Schädelin, Aysenur Akbulut, Henning Müller, Muhamed Barakovic, Lester Melie-Garcia, Meritxell Bach Cuadra, Cristina Granziera
Publikováno v:
NeuroImage: Clinical, Vol 39, Iss , Pp 103491- (2023)
Introduction: Over the past few years, the deep learning community has developed and validated a plethora of tools for lesion detection and segmentation in Multiple Sclerosis (MS). However, there is an important gap between validating models technica
Externí odkaz:
https://doaj.org/article/1f1c6e70d8c84dcba420fa64e3c6f4b3
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 3, Iss 2, Pp 374-391 (2021)
The diffused practice of pre-training Convolutional Neural Networks (CNNs) on large natural image datasets such as ImageNet causes the automatic learning of invariance to object scale variations. This, however, can be detrimental in medical imaging,
Externí odkaz:
https://doaj.org/article/6943815eede241ea85a809787bfbb1fd
Publikováno v:
European Radiology Experimental, Vol 4, Iss 1, Pp 1-9 (2020)
Abstract Radiomics, artificial intelligence, and deep learning figure amongst recent buzzwords in current medical imaging research and technological development. Analysis of medical big data in assessment and follow-up of personalised treatments has
Externí odkaz:
https://doaj.org/article/f0a0754884cf45daa2dd9317afc62c65