Pseudo-Label-Assisted Self-Organizing Maps for Brain Tissue Segmentation in Magnetic Resonance Imaging

2022 ◽  
Author(s):  
Jonas Grande-Barreto ◽  
Pilar Gómez-Gil
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Tissue ◽  
Resonance Imaging ◽  
Tissue Segmentation ◽  
Self Organizing Maps ◽  
Brain Tissue Segmentation ◽  
Self Organizing

scholarly journals Probabilistic Brain Tissue Segmentation in Neonatal Magnetic Resonance Imaging

2008 ◽  
Vol 63 (2) ◽  
pp. 158-163 ◽  
Author(s):  
Petronella Anbeek ◽  
Koen L Vincken ◽  
Floris Groenendaal ◽  
Annemieke Koeman ◽  
Matthias J P van Osch ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Tissue ◽  
Resonance Imaging ◽  
Tissue Segmentation ◽  
Brain Tissue Segmentation

Unsupervised time course analysis of functional magnetic resonance imaging (fMRI) using self-organizing maps (SOMs)

1999 ◽  
Author(s):  
Stephan G. Erberich ◽  
Matthias Fellenberg ◽  
Timo Krings ◽  
Stefan Kemeny ◽  
Wolfgang Reith ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Time Course ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Self Organizing Maps ◽  
Self Organizing

Analysis of neoplastic lesions in magnetic resonance imaging using self-organizing maps

2015 ◽  
Vol 359 (1-2) ◽  
pp. 78-83 ◽  
Author(s):  
Paulo Afonso Mei ◽  
Cleyton de Carvalho Carneiro ◽  
Stephen J. Fraser ◽  
Li Li Min ◽  
Fabiano Reis
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Resonance Imaging ◽  
Self Organizing Maps ◽  
Neoplastic Lesions ◽  
Self Organizing

Brain Tissue Volume Measurement from Magnetic Resonance Imaging A Phantom Study

1993 ◽  
Vol 28 (10) ◽  
pp. 890-895 ◽  
Author(s):  
HENRY RUSINEK ◽  
RAMESH CHANDRA
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Tissue ◽  
Volume Measurement ◽  
Phantom Study ◽  
Resonance Imaging ◽  
Tissue Volume

Inter- and intraoperator reliability of brain tissue measures using magnetic resonance imaging

2003 ◽  
Vol 253 (6) ◽  
pp. 301-306 ◽  
Author(s):  
Gaku Okugawa ◽  
Katsunori Takase ◽  
Kenji Nobuhara ◽  
Tsunetaka Yoshida ◽  
Tomohisa Minami ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Tissue ◽  
Resonance Imaging

scholarly journals Modern Imaging Modalities in the Assessment of Acute Stroke

Folia Medica ◽  
2014 ◽  
Vol 56 (2) ◽  
pp. 81-87 ◽  
Author(s):  
Dora K. Zlatareva ◽  
Nikoleta I. Traykova
Keyword(s):  
Magnetic Resonance Imaging ◽  
Computed Tomography ◽  
At Risk ◽  
Magnetic Resonance ◽  
Acute Stroke ◽  
Brain Tissue ◽  
Ct Angiography ◽  
Imaging Modalities ◽  
Minor Stroke ◽  
Resonance Imaging

Abstract The AIM of this review was to present the modern concepts of diagnostic imaging in acute stroke. Neuroimaging in acute stroke aims at diagnosing the condition as early as possible and assessing the extent of parenchymal perfusion and the intracranial vessels patency. A modern approach would involve a combination of various imaging modalities as multidetector computed tomography and high field magnetic resonance imaging. A non-enhanced computed tomography (CT) is used to detect hemorrhage or to identify early signs of ischemic stroke. CT angiography finds evidence of intravascular thrombi or significant stenoses, and CT perfusion displays brain tissue at risk of irreversible alterations that can be salvaged therapeutically. Magnetic resonance imaging (MRI) is a more sensitive modality than CT in diagnosing acute brain ischemia. MR diffusion-weighted imaging is more sensitive than conventional MR sequences in hyperacute stage. MR angiography as a non-invasive and non-ionizing imaging method is used as an alternative modality to CT angiography. To find brain tissue at risk diffusion- and perfusion-weighted magnetic resonance imaging modalities are used. The authors present briefly the modern neuroimaging modalities used in patients with transient ischemic attack, minor stroke and venous infarction. By combining different imaging techniques in a multimodal approach we can acquire the information necessary for therapeutic planning and differentiate patients who need thrombolysis.

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