Automated lesion segmentation with BIANCA: Impact of population-level features, classification algorithm and locally adaptive thresholding

White matter hyperintensities (WMH) or white matter lesions exhibit high variability in their characteristics both at population- and subject-level, making their detection a challenging task. Population-level factors such as age, vascular risk factors and neurodegenerative diseases affect lesion loa...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	NeuroImage (Orlando, Fla.) Ročník 202; s. 116056
Hlavní autori:	Sundaresan, Vaanathi, Zamboni, Giovanna, Le Heron, Campbell, Rothwell, Peter M., Husain, Masud, Battaglini, Marco, De Stefano, Nicola, Jenkinson, Mark, Griffanti, Ludovica
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Inc 15.11.2019 Elsevier Limited Academic Press
Predmet:	Age Age Factors Aged Aged, 80 and over Aging Algorithms Artificial intelligence Automation Brain Diseases - diagnostic imaging Classification Datasets Female Humans Image Interpretation, Computer-Assisted - methods Learning algorithms Lesion probability map Lesion segmentation Lesions Leukoencephalopathy Load Machine Learning Magnetic Resonance Imaging - methods Male Methods Middle Aged Neural networks Neurodegenerative diseases Neuroimaging - methods Pattern Recognition, Automated - methods Population Probability Risk factors Segmentation Spatial distribution Structural MRI Substantia alba Thresholding Vascular diseases White Matter - diagnostic imaging White matter hyperintensities Structural MRI Lesion probability map White matter hyperintensities Lesion segmentation Thresholding Machine learning
ISSN:	1053-8119, 1095-9572, 1095-9572
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!