Detail publikace
Automated 3D Brain Tumor Edema Segmentation in FLAIR MRI
DVOŘÁK, P. BARTUŠEK, K.
Originální název
Automated 3D Brain Tumor Edema Segmentation in FLAIR MRI
Anglický název
Automated 3D Brain Tumor Edema Segmentation in FLAIR MRI
Jazyk
en
Originální abstrakt
The aim of this work is to develop a fully automatic method for peritumoral region segmentation in 3D FLAIR MRI. FLAIR was selected because of the visibility and manifestation of tumor edemas in this image type. The main reason for the edema segmentation is the tumor classification. This will be carried out by applying the resulting mask to perfusion MR images. Since perfusion images are of a very low contrast, the pathological area, it means the tumor and a potential edema around it, has to be detected and segmented in another type of MR images.
Anglický abstrakt
The aim of this work is to develop a fully automatic method for peritumoral region segmentation in 3D FLAIR MRI. FLAIR was selected because of the visibility and manifestation of tumor edemas in this image type. The main reason for the edema segmentation is the tumor classification. This will be carried out by applying the resulting mask to perfusion MR images. Since perfusion images are of a very low contrast, the pathological area, it means the tumor and a potential edema around it, has to be detected and segmented in another type of MR images.
Dokumenty
BibTex
@misc{BUT100785,
author="Pavel {Dvořák} and Karel {Bartušek}",
title="Automated 3D Brain Tumor Edema Segmentation in FLAIR MRI",
annote="The aim of this work is to develop a fully automatic method for peritumoral region segmentation in 3D FLAIR MRI. FLAIR was selected because of the visibility and manifestation of tumor edemas in this image type. The main reason for the edema segmentation is the tumor classification. This will be carried out by applying the resulting mask to perfusion MR images. Since perfusion images are of a very low contrast, the pathological area, it means the tumor and a potential edema around it, has to be detected and segmented in another type of MR images.",
address="Springer",
chapter="100785",
doi="10.1007/s10334-013-0385-4",
institution="Springer",
number="1 Supplement",
year="2013",
month="october",
pages="489--490",
publisher="Springer",
type="abstract"
}