Crohn's disease tissue segmentation from abdominal MRI using semantic information and graph cuts

Dwarikanath Mahapatra, Peter J. Schuffler, Jeroen A.W. Tielbeek, Franciscus M. Vos, Joachim M. Buhmann

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

8 Zitate (Scopus)

Abstract

We propose a graph cut based method to segment regions in abdominal magnetic resonance (MR) images affected with Crohn's disease (CD). Intensity, texture, curvature and context information are used with random forest (RF) classifiers to calculate probability maps for graph cut segmentation. The RF classifiers also provide semantic information used to design a novel smoothness cost. Experimental results on 26 real patient data shows our method accurately segments the diseased areas. Inclusion of semantic information significantly improves segmentation accuracy and its importance is reflected in quantitative measures and visual results.

OriginalspracheEnglisch
TitelISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging
UntertitelFrom Nano to Macro
Seiten358-361
Seitenumfang4
DOIs
PublikationsstatusVeröffentlicht - 2013
Extern publiziertJa
Veranstaltung2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013 - San Francisco, CA, USA/Vereinigte Staaten
Dauer: 7 Apr. 201311 Apr. 2013

Publikationsreihe

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (elektronisch)1945-8452

Konferenz

Konferenz2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013
Land/GebietUSA/Vereinigte Staaten
OrtSan Francisco, CA
Zeitraum7/04/1311/04/13

Fingerprint

Untersuchen Sie die Forschungsthemen von „Crohn's disease tissue segmentation from abdominal MRI using semantic information and graph cuts“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren