Automatic segmentation of abdominal organs and adipose tissue compartments in water-fat MRI: Application to weight-loss in obesity.

Shen, Jun; Baum, Thomas; Cordes, Christian; Ott, Beate; Skurk, Thomas; Kooijman, Hendrik; Rummeny, Ernst J; Hauner, Hans; Menze, Bjoern H; Karampinos, Dimitrios C

doi:10.1016/j.ejrad.2016.06.006

Benutzer: Gast

Else Kröner-Fresenius-Zentrum für Ernährungsmedizin - Klinik für Ernährungsmedizin

Zurück
Zurück zum Anfang der Trefferliste
Dauerhafter Link zum angezeigten Objekt

Wenn Sie Schwierigkeiten haben, das Dokument zu öffnen, versuchen Sie auch bitte diesen Link

Titel:: Automatic segmentation of abdominal organs and adipose tissue compartments in water-fat MRI: Application to weight-loss in obesity.
Dokumenttyp:: Journal Article; Article
Autor(en):: Shen, Jun; Baum, Thomas; Cordes, Christian; Ott, Beate; Skurk, Thomas; Kooijman, Hendrik; Rummeny, Ernst J; Hauner, Hans; Menze, Bjoern H; Karampinos, Dimitrios C
Abstract:: To develop a fully automatic algorithm for abdominal organs and adipose tissue compartments segmentation and to assess organ and adipose tissue volume changes in longitudinal water-fat magnetic resonance imaging (MRI) data.Axial two-point Dixon images were acquired in 20 obese women (age range 24-65, BMI 34.9±3.8kg/m(2)) before and after a four-week calorie restriction. Abdominal organs, subcutaneous adipose tissue (SAT) compartments (abdominal, anterior, posterior), SAT regions along the feet-head direction and regional visceral adipose tissue (VAT) were assessed by a fully automatic algorithm using morphological operations and a multi-atlas-based segmentation method.The accuracy of organ segmentation represented by Dice coefficients ranged from 0.672±0.155 for the pancreas to 0.943±0.023 for the liver. Abdominal SAT changes were significantly greater in the posterior than the anterior SAT compartment (-11.4%±5.1% versus -9.5%±6.3%, p<0.001). The loss of VAT that was not located around any organ (-16.1%±8.9%) was significantly greater than the loss of VAT 5cm around liver, left and right kidney, spleen, and pancreas (p<0.05).The presented fully automatic algorithm showed good performance in abdominal adipose tissue and organ segmentation, and allowed the detection of SAT and VAT subcompartments changes during weight loss.
Zeitschriftentitel:: Eur J Radiol
Jahr:: 2016
Band / Volume:: 85
Heft / Issue:: 9
Seitenangaben Beitrag:: 1613-21
Nachgewiesen in:: Web of Science
Sprache:: eng
Volltext / DOI:: doi:10.1016/j.ejrad.2016.06.006
PubMed:: http://view.ncbi.nlm.nih.gov/pubmed/27501897
Print-ISSN:: 0720-048X
TUM Einrichtung:: Else Kröner-Fresenius-Zentrum für Ernährungsmedizin - Klinik für Ernährungsmedizin
BibTeX