Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Jeanny Pan"'
Autor:
Johannes Hofmanninger, Forian Prayer, Jeanny Pan, Sebastian Röhrich, Helmut Prosch, Georg Langs
Publikováno v:
European Radiology Experimental, Vol 4, Iss 1, Pp 1-13 (2020)
Abstract Background Automated segmentation of anatomical structures is a crucial step in image analysis. For lung segmentation in computed tomography, a variety of approaches exists, involving sophisticated pipelines trained and validated on differen
Externí odkaz:
https://doaj.org/article/6b04fd0a1dc247348bfabb653d3067d0
Autor:
Jeanny Pan, Johannes Hofmanninger, Karl-Heinz Nenning, Florian Prayer, Sebastian Röhrich, Nicola Sverzellati, Venerino Poletti, Sara Tomassetti, Michael Weber, Helmut Prosch, Georg Langs
Publikováno v:
Pan, J, Hofmanninger, J, Nenning, K H, Prayer, F, Röhrich, S, Sverzellati, N, Poletti, V, Tomassetti, S, Weber, M, Prosch, H & Langs, G 2023, ' Unsupervised machine learning identifies predictive progression markers of IPF ', European Radiology, vol. 33, no. 2, pp. 925-935 . https://doi.org/10.1007/s00330-022-09101-x
Objectives To identify and evaluate predictive lung imaging markers and their pathways of change during progression of idiopathic pulmonary fibrosis (IPF) from sequential data of an IPF cohort. To test if these imaging markers predict outcome. Method
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::85b0379026b19d13015b51f541e6185c
https://pure.au.dk/portal/da/publications/unsupervised-machine-learning-identifies-predictive-progression-markers-of-ipf(58ba3144-3971-4e05-9cea-e9af8d3e4544).html
https://pure.au.dk/portal/da/publications/unsupervised-machine-learning-identifies-predictive-progression-markers-of-ipf(58ba3144-3971-4e05-9cea-e9af8d3e4544).html
Autor:
Johannes Hofmanninger, Helmut Prosch, Jeanny Pan, Florian Prayer, Georg Langs, Daria Kifjak, Michael Weber, Sebastian Röhrich, Alexander Willenpart
Publikováno v:
Methods. 188:98-104
Objectives To investigate the intra- and inter-scanner repeatability and reproducibility of CT radiomics features (RF) of fibrosing interstitial lung disease (fILD). Methods For this prospective, IRB-approved test-retest study, CT data of sixty fILD
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::590a6146c581a5e559334bee477ae4e8
https://doi.org/10.1016/j.ymeth.2020.08.007
https://doi.org/10.1016/j.ymeth.2020.08.007
Autor:
Florian Prayer, Johannes Hofmanninger, Georg Langs, Helmut Prosch, Sebastian Röhrich, Jeanny Pan
Publikováno v:
European Radiology Experimental
European Radiology Experimental, Vol 4, Iss 1, Pp 1-13 (2020)
European Radiology Experimental, Vol 4, Iss 1, Pp 1-13 (2020)
Automated segmentation of anatomical structures is a crucial step in image analysis. For lung segmentation in computed tomography, a variety of approaches exist, involving sophisticated pipelines trained and validated on different datasets. However,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f15e3b73a70f8a53170b8b223ad09bc
http://europepmc.org/articles/PMC7438418
http://europepmc.org/articles/PMC7438418
Autor:
Jeanny Pan, Georg Langs, Florian Prayer, H. Prosch, Sebastian Röhrich, Johannes Hofmanninger, Christian J. Herold
Publikováno v:
Der Radiologe
Machine learning is rapidly gaining importance in radiology. It allows for the exploitation of patterns in imaging data and in patient records for a more accurate and precise quantification, diagnosis, and prognosis. Here, we outline the basics of ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ecf545001fed32b554809ee2710114aa
http://europepmc.org/articles/PMC6244522
http://europepmc.org/articles/PMC6244522