Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling

Enrico Grisan

doi:10.1109/ISBI.2017.7950637

Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling

Enrico Grisan

Chemical and Energy Engineering

Research output: Contribution to conference › Paper

Abstract

Cortical Thickness (CTh) estimation from Magnetic Resonance Imaging (MRI) data of Multiple Sclerosis (MS) patients is biased at variable extent by the presence of white matter lesions. To overcome this limitation, several methods have been developed. In this study, we evaluate the impact on CTh measurements of different lesion corrections obtained combining three lesion segmentations (manual or automatic) with three intensity filling methods at whole brain and regional scale. © 2017 IEEE.

Original language	English
DOIs	https://doi.org/10.1109/ISBI.2017.7950637
Publication status	Published - 18 Jun 2017
Event	2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) - Duration: 19 Jun 2017 → …

Conference

Conference	2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)
Period	19/06/17 → …

Keywords

cortical thickness
lesion segmentation
MRI
multiple sclerosis
lesion filling

Access to Document

10.1109/ISBI.2017.7950637Licence: CC BY 4.0

Cite this

@conference{4dd15b062e684947a15c34909b18d9f2,

title = "Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling",

abstract = "Cortical Thickness (CTh) estimation from Magnetic Resonance Imaging (MRI) data of Multiple Sclerosis (MS) patients is biased at variable extent by the presence of white matter lesions. To overcome this limitation, several methods have been developed. In this study, we evaluate the impact on CTh measurements of different lesion corrections obtained combining three lesion segmentations (manual or automatic) with three intensity filling methods at whole brain and regional scale. {\textcopyright} 2017 IEEE.",

keywords = "cortical thickness, lesion segmentation, MRI, multiple sclerosis, lesion filling",

author = "Enrico Grisan",

year = "2017",

month = jun,

day = "18",

doi = "10.1109/ISBI.2017.7950637",

language = "English",

note = "2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) ; Conference date: 19-06-2017",

}

TY - CONF

T1 - Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling

AU - Grisan, Enrico

PY - 2017/6/18

Y1 - 2017/6/18

N2 - Cortical Thickness (CTh) estimation from Magnetic Resonance Imaging (MRI) data of Multiple Sclerosis (MS) patients is biased at variable extent by the presence of white matter lesions. To overcome this limitation, several methods have been developed. In this study, we evaluate the impact on CTh measurements of different lesion corrections obtained combining three lesion segmentations (manual or automatic) with three intensity filling methods at whole brain and regional scale. © 2017 IEEE.

AB - Cortical Thickness (CTh) estimation from Magnetic Resonance Imaging (MRI) data of Multiple Sclerosis (MS) patients is biased at variable extent by the presence of white matter lesions. To overcome this limitation, several methods have been developed. In this study, we evaluate the impact on CTh measurements of different lesion corrections obtained combining three lesion segmentations (manual or automatic) with three intensity filling methods at whole brain and regional scale. © 2017 IEEE.

KW - cortical thickness

KW - lesion segmentation

KW - MRI

KW - multiple sclerosis

KW - lesion filling

U2 - 10.1109/ISBI.2017.7950637

DO - 10.1109/ISBI.2017.7950637

M3 - Paper

T2 - 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

Y2 - 19 June 2017

ER -

Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this