Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Lukas Hirsch"'
Autor:
Maximilian Nentwich, Marcin Leszczynski, Brian E. Russ, Lukas Hirsch, Noah Markowitz, Kaustubh Sapru, Charles E. Schroeder, Ashesh D. Mehta, Stephan Bickel, Lucas C. Parra
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-17 (2023)
Abstract Our continuous visual experience in daily life is dominated by change. Previous research has focused on visual change due to stimulus motion, eye movements or unfolding events, but not their combined impact across the brain, or their interac
Externí odkaz:
https://doaj.org/article/fa25a0f493774ec598aad7b725c3a3ce
Autor:
Maximilian Nentwich, Marcin Leszczynski, Brian E. Russ, Lukas Hirsch, Noah Markowitz, Kaustubh Sapru, Charles E. Schroeder, Ashesh Mehta, Stephan Bickel, Lucas C Parra
Our continuous visual experience in daily life is dominated by change. Previous research has focused on visual change due to stimulus motion, eye movements or unfolding events, but not their combined impact across the brain, or their interactions wit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21a139a39a765c4357ab87129f400a72
https://doi.org/10.1101/2022.06.20.496467
https://doi.org/10.1101/2022.06.20.496467
Radiologist-Level Performance by Using Deep Learning for Segmentation of Breast Cancers on MRI Scans
Autor:
Lukas Hirsch, Yu Huang, Shaojun Luo, Carolina Rossi Saccarelli, Roberto Lo Gullo, Isaac Daimiel Naranjo, Almir G. V. Bitencourt, Natsuko Onishi, Eun Sook Ko, Doris Leithner, Daly Avendano, Sarah Eskreis-Winkler, Mary Hughes, Danny F. Martinez, Katja Pinker, Krishna Juluru, Amin E. El-Rowmeim, Pierre Elnajjar, Elizabeth A. Morris, Hernan A. Makse, Lucas C. Parra, Elizabeth J. Sutton
Publikováno v:
Radiology: Artificial Intelligence. 4
Purpose: To develop a deep network architecture that would achieve fully automated radiologist-level segmentation of cancers at breast MRI. Materials and Methods: In this retrospective study, 38229 examinations (composed of 64063 individual breast sc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cdddbcaced5899fc07f989a974d684af
https://doi.org/10.1148/ryai.200231
https://doi.org/10.1148/ryai.200231
Autor:
Lionel Naccache, Frédéric Faugeras, Sophie Demeret, Bertrand Hermann, Nicolas Weiss, Lucas C. Parra, Federico Raimondo, Mélanie Denis-Valente, Benjamin Rohaut, Denis A. Engemann, Jacobo D. Sitt, Lukas Hirsch, Yu Huang, Pauline Pérez
Publikováno v:
Scientific Reports
Scientific Reports, Nature Publishing Group, 2020, ⟨10.1101/612309⟩
Scientific Reports, 2020, ⟨10.1101/612309⟩
Scientific Reports, Vol 10, Iss 1, Pp 1-16 (2020)
Scientific Reports, Nature Publishing Group, 2020, ⟨10.1101/612309⟩
Scientific Reports, 2020, ⟨10.1101/612309⟩
Scientific Reports, Vol 10, Iss 1, Pp 1-16 (2020)
Severe brain injuries can lead to long-lasting disorders of consciousness (DoC) such as vegetative state/unresponsive wakefulness syndrome (VS/UWS) or minimally conscious state (MCS). While behavioral assessment remains the gold standard to determine
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb50606e040728ed4863a0e15f494f08
https://hal.archives-ouvertes.fr/hal-02107872
https://hal.archives-ouvertes.fr/hal-02107872
Publikováno v:
J Med Imaging (Bellingham)
Purpose: Conventional automated segmentation of the head anatomy in magnetic resonance images distinguishes different brain and nonbrain tissues based on image intensities and prior tissue probability maps (TPMs). This works well for normal head anat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c8770ae1417f8b2a7fa72dfa74194bf
http://arxiv.org/abs/1905.10010
http://arxiv.org/abs/1905.10010