A novel combined level set model for automatic MR image segmentation

Current Directions in Biomedical Engineering, vol. 6, pp. 20–23

Abstract

Abstract Medical image processing comes along with object segmentation, which is one of the most important tasks in that field. Nevertheless, noise and intensity inhomogeneity in magnetic resonance images challenge the segmentation procedure. The level set method has been widely used in object detection. The flexible integration of energy terms affords the level set method to deal with variable difficulties. In this paper, we introduce a novel combined level set model that mainly cooperates with an edge detector and a local region intensity descriptor. The noise and intensity inhomogeneities are eliminated by the local region intensity descriptor. The edge detector helps the level set model to locate the object boundaries more precisely. The proposed model was validated on synthesized images and magnetic resonance images of in vivo wrist bones. Comparing with the ground truth, the proposed method reached a Dice similarity coefficient of > 0.99 on all image tests, while the compared segmentation approaches failed the segmentations. The presented combined level set model can be used for the object segmentation in magnetic resonance images.

Authors 4

1. Sven Nebelung

   Düsseldorf University Hospital

   Affiliation as printed

   Institute of Diagnostic and Interventional Radiology, University Hospital Düsseldorf, Düsseldorf , Germany

2. Björn Rath

   Klinikum Wels-Grieskirchen

   Affiliation as printed

   Department of Orthopaedic Surgery, Klinikum Wels- Grieskirchen, Wels , Austria

3. Markus Tingart Aachen Department of Orthopaedic Surgery

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Department of Orthopaedic Surgery, RWTH Aachen University Clinic, Aachen , Germany

4. Jörg Eschweiler Aachen Department of Orthopaedic Surgery

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Department of Orthopaedic Surgery, RWTH Aachen University Clinic, Aachen , Germany