Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Elise, Sandsmark"'
Autor:
Maria K. Andersen, Sebastian Krossa, Elise Midtbust, Christine A. Pedersen, Maximilian Wess, Therese S. Høiem, Trond Viset, Øystein Størkersen, Ingunn Nervik, Elise Sandsmark, Helena Bertilsson, Guro F. Giskeødegård, Morten B. Rye, May-Britt Tessem
Publikováno v:
Communications Biology, Vol 7, Iss 1, Pp 1-15 (2024)
Abstract Prostate tumor heterogeneity is a major obstacle when studying the biological mechanisms of molecular markers. Increased gene expression levels of secreted frizzled-related protein 4 (SFRP4) is a biomarker in aggressive prostate cancer. To u
Externí odkaz:
https://doaj.org/article/cfb7b7c0fee44d1a91ff052f18aee172
Autor:
Ingrid Framås Syversen, Mattijs Elschot, Elise Sandsmark, Helena Bertilsson, Tone Frost Bathen, Pål Erik Goa
Publikováno v:
PLoS ONE, Vol 16, Iss 5, p e0252387 (2021)
BackgroundMagnetic resonance imaging (MRI) is essential in the detection and staging of prostate cancer. However, improved tools to distinguish between low-risk and high-risk cancer are needed in order to select the appropriate treatment.PurposeTo in
Externí odkaz:
https://doaj.org/article/9a8fbd822d7b4f8bbed928b237a56986
Autor:
Mohammed R. S. Sunoqrot, Kirsten M. Selnæs, Elise Sandsmark, Sverre Langørgen, Helena Bertilsson, Tone F. Bathen, Mattijs Elschot
Publikováno v:
Diagnostics, Vol 11, Iss 9, p 1690 (2021)
Volume of interest segmentation is an essential step in computer-aided detection and diagnosis (CAD) systems. Deep learning (DL)-based methods provide good performance for prostate segmentation, but little is known about the reproducibility of these
Externí odkaz:
https://doaj.org/article/7c7dbb665f3e4953a8cdc0dfca74dee3
Autor:
Mohammed R. S. Sunoqrot, Kirsten M. Selnæs, Elise Sandsmark, Gabriel A. Nketiah, Olmo Zavala-Romero, Radka Stoyanova, Tone F. Bathen, Mattijs Elschot
Publikováno v:
Diagnostics, Vol 10, Iss 9, p 714 (2020)
Computer-aided detection and diagnosis (CAD) systems have the potential to improve robustness and efficiency compared to traditional radiological reading of magnetic resonance imaging (MRI). Fully automated segmentation of the prostate is a crucial s
Externí odkaz:
https://doaj.org/article/0cf7d7df410e405b92bf59f478f3b2e4
Autor:
Morteza Esmaeili, Nassim Tayari, Tom Scheenen, Mattijs Elschot, Elise Sandsmark, Helena Bertilsson, Arend Heerschap, Kirsten M. Selnæs, Tone F. Bathen
Publikováno v:
Frontiers in Oncology, Vol 8 (2018)
Purpose: To investigate the associations of metabolite levels derived from magnetic resonance spectroscopic imaging (MRSI) and 18F-fluciclovine positron emission tomography (PET) with prostate tissue characteristics.Methods: In a cohort of 19 high-ri
Externí odkaz:
https://doaj.org/article/25a99718ff574419a4d04c990e19bcac
Autor:
Kaia Ingerdatter Sørland, Mohammed R. S. Sunoqrot, Elise Sandsmark, Sverre Langørgen, Helena Bertilsson, Christopher G. Trimble, Gigin Lin, Kirsten M. Selnæs, Pål E. Goa, Tone F. Bathen, Mattijs Elschot
Publikováno v:
Magnetic Resonance Materials in Physics, Biology and Medicine
Objective Signal intensity normalization is necessary to reduce heterogeneity in T2-weighted (T2W) magnetic resonance imaging (MRI) for quantitative analysis of multicenter data. AutoRef is an automated dual-reference tissue normalization method that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f603f41b5423829ba667332d27ee001
https://pubmed.ncbi.nlm.nih.gov/35150363
https://pubmed.ncbi.nlm.nih.gov/35150363
Autor:
Tone Frost Bathen, Elise Sandsmark, Kirsten Margrete Selnæs, Mohammed R. S. Sunoqrot, Helena Bertilsson, Sverre Langørgen, Mattijs Elschot
Publikováno v:
Diagnostics
Volume 11
Issue 9
Diagnostics (Basel)
Diagnostics, Vol 11, Iss 1690, p 1690 (2021)
Volume 11
Issue 9
Diagnostics (Basel)
Diagnostics, Vol 11, Iss 1690, p 1690 (2021)
Volume of interest segmentation is an essential step in computer-aided detection and diagnosis (CAD) systems. Deep learning (DL)-based methods provide good performance for prostate segmentation, but little is known about the reproducibility of these
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3084f1f439473f6b7f9b0c54a0367416
https://pubmed.ncbi.nlm.nih.gov/34574031
https://pubmed.ncbi.nlm.nih.gov/34574031
Autor:
Pål Erik Goa, Tone Frost Bathen, Ingrid Framås Syversen, Mattijs Elschot, Elise Sandsmark, Helena Bertilsson
Publikováno v:
PLOS ONE
e0252387
PLoS ONE
PLoS ONE, Vol 16, Iss 5, p e0252387 (2021)
e0252387
PLoS ONE
PLoS ONE, Vol 16, Iss 5, p e0252387 (2021)
Background Magnetic resonance imaging (MRI) is essential in the detection and staging of prostate cancer. However, improved tools to distinguish between low-risk and high-risk cancer are needed in order to select the appropriate treatment. Purpose To
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b229b21b49eea7c3e4fb0c7f6b7cfdd
https://hdl.handle.net/11250/2758530
https://hdl.handle.net/11250/2758530
Autor:
Elise Sandsmark, Kirsten Margrete Selnæs, Olmo Zavala-Romero, Tone Frost Bathen, Mattijs Elschot, Gabriel Nketiah, Mohammed R. S. Sunoqrot, Radka Stoyanova
Publikováno v:
Diagnostics (Basel)
Diagnostics, Vol 10, Iss 714, p 714 (2020)
Diagnostics; Volume 10; Issue 9; Pages: 714
Diagnostics
Diagnostics, Vol 10, Iss 714, p 714 (2020)
Diagnostics; Volume 10; Issue 9; Pages: 714
Diagnostics
Computer-aided detection and diagnosis (CAD) systems have the potential to improve robustness and efficiency compared to traditional radiological reading of magnetic resonance imaging (MRI). Fully automated segmentation of the prostate is a crucial s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6dd55ad216406d20eaa7a6e9f782a40
https://hdl.handle.net/11250/2679703
https://hdl.handle.net/11250/2679703
Autor:
Elin Richardsen, Trond Viset, Morten Beck Rye, Alan J. Wright, Anna M. Bofin, May-Britt Tessem, Elise Sandsmark, Tone Frost Bathen, Finn Drabløs, Helena Bertilsson, Ailin Falkmo Hansen, Kirsten Margrete Selnæs
Publikováno v:
Oncotarget
OncoTarget
OncoTarget
// Elise Sandsmark 1 , Ailin Falkmo Hansen 1 , Kirsten M. Selnaes 1 , Helena Bertilsson 2, 3 , Anna M. Bofin 4 , Alan J. Wright 5 , Trond Viset 6 , Elin Richardsen 7, 8 , Finn Drablos 3 , Tone F. Bathen 1 , May-Britt Tessem 1, * , Morten B. Rye 2, 3,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb3123f5415a6338bcdeb7169d079b25
https://doi.org/10.18632/oncotarget.14161
https://doi.org/10.18632/oncotarget.14161