Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Kumpei Ikuta"'
Publikováno v:
IEEE Access, Vol 11, Pp 116903-116918 (2023)
A subject’s head position in magnetic resonance imaging (MRI) scanners can vary significantly with the imaging environment and disease status. This variation is known to influence the accuracy of skull stripping (SS), a method to extract the brain
Externí odkaz:
https://doaj.org/article/524257960d34469ba93b266e7d4ca88c
Publikováno v:
IEEE Access, Vol 9, Pp 165326-165340 (2021)
To build a robust and practical content-based image retrieval (CBIR) system applicable to clinical brain MRI databases, we propose a new framework, disease-oriented image embedding with pseudo-scanner standardization (DI-PSS). It consists of two core
Externí odkaz:
https://doaj.org/article/1fcba5958f47423db0c314aeaf745dfb
Publikováno v:
IEEE Access, Vol 9, Pp 165326-165340 (2021)
To build a robust and practical content-based image retrieval (CBIR) system that is applicable to a clinical brain MRI database, we propose a new framework -- Disease-oriented image embedding with pseudo-scanner standardization (DI-PSS) -- that consi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cfbb00a05e953c5fbd3687d48a5f8cb2
https://doi.org/10.1109/access.2021.3129105
https://doi.org/10.1109/access.2021.3129105
Autor:
Kumpei Ikuta, Hitoshi Iyatomi, Kenichi Oishi, on behalf of the Alzheimer’s Disease Neuroimaging Initiative
Publikováno v:
AAAI Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::79b01ea70429e7ec33d90a53d9bf72b9
https://doi.org/10.3390/cmsf2022003007
https://doi.org/10.3390/cmsf2022003007
Content-based image retrieval (CBIR) systems are an emerging technology that supports reading and interpreting medical images. Since 3D brain MR images are high dimensional, dimensionality reduction is necessary for CBIR using machine learning techni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc7216156a3c4d7b2513635aaca0251f
