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of 316
pro vyhledávání: '"Smedby, örjan"'
Significant advances have been made toward building accurate automatic segmentation models for adult gliomas. However, the performance of these models often degrades when applied to pediatric glioma due to their imaging and clinical differences (doma
Externí odkaz:
http://arxiv.org/abs/2406.16848
Alzheimer's Disease and normal aging are both characterized by brain atrophy. The question of whether AD-related brain atrophy represents accelerated aging or a neurodegeneration process distinct from that in normal aging remains unresolved. Moreover
Externí odkaz:
http://arxiv.org/abs/2311.08176
Autor:
Astaraki, Mehdi, De Benetti, Francesca, Yeganeh, Yousef, Toma-Dasu, Iuliana, Smedby, Örjan, Wang, Chunliang, Navab, Nassir, Wendler, Thomas
Robust and accurate detection and segmentation of heterogenous tumors appearing in different anatomical organs with supervised methods require large-scale labeled datasets covering all possible types of diseases. Due to the unavailability of such ric
Externí odkaz:
http://arxiv.org/abs/2305.12358
Autor:
Tisell, Anders, Dahlqvist Leinhard, Olof, Warntjes, Jan Bertus Marcel, Aalto, Arne, Smedby, Örjan, Landtblom, Anne-Marie, Lundberg, Peter
In Multiple Sclerosis (MS) the relationship between disease process in normal-appearing white matter (NAWM) and the development of white matter lesions is not well understood. In this study we used single voxel proton ‘Quantitative Magnetic Resonan
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-85924
Autor:
Bendazzoli, Simone, Brusini, Irene, Astaraki, Mehdi, Persson, Mats, Yu, Jimmy, Connolly, Bryan, Nyrén, Sven, Strand, Fredrik, Smedby, Örjan, Wang, Chunliang
Segmentation of COVID-19 lesions from chest CT scans is of great importance for better diagnosing the disease and investigating its extent. However, manual segmentation can be very time consuming and subjective, given the lesions' large variation in
Externí odkaz:
http://arxiv.org/abs/2012.14752
Autor:
Brusini, Irene, Padilla, Daniel Ferreira, Barroso, José, Skoog, Ingmar, Smedby, Örjan, Westman, Eric, Wang, Chunliang
Brain MRI segmentation results should always undergo a quality control (QC) process, since automatic segmentation tools can be prone to errors. In this work, we propose two deep learning-based architectures for performing QC automatically. First, we
Externí odkaz:
http://arxiv.org/abs/2005.13987
Autor:
Dohlmar, Frida, Morén, Björn, Sandborg, Michael, Smedby, Örjan, Valdman, Alexander, Larsson, Torbjörn, Carlsson Tedgren, Åsa
Publikováno v:
In Brachytherapy May-June 2023 22(3):407-415
Publikováno v:
In European Journal of Radiology Open 2023 10
Akademický článek
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Autor:
Brusini, Irene, MacNicol, Eilidh, Kim, Eugene, Smedby, Örjan, Wang, Chunliang, Westman, Eric, Veronese, Mattia, Turkheimer, Federico, Cash, Diana
Publikováno v:
In Neurobiology of Aging January 2022 109:204-215