Nowadays, the brain tumor detection and segmentation in MR images is a de-veloping issue. There are many research teams producing di®erent and interesting methods andalgorithms for this particular task of medical image processing. Many of them are semi-automatic,but the aim of current research, and of this work, is to ¯nd a fully automatic method.This paper focuses on the automatic edema segmentation in FLAIR images. This type of contrastimages was selected because of the visibility and manifestation of edema in this image type. Sincein axial plane of healthy brain, the approximate left-right symmetry exists, it is used as the priorknowledge for searching the approximate edema location. It is assumed that the edema is notlocated symmetrically in both hemispheres, which is met in most cases. For the detection, themulti-resolution approach is used. Since the edemas manifest as a hyperintense area in FLAIRimages, it is extracted using thresholding. For the automatic determination of the threshold, theOtsu's algorithm is used. This work does not deal with the tumor presence detection. One of ourprevious work focuses on this topic. The main reason for the edema segmentation is for the tumorclassi¯cation. This will be carried out by applying the resulting mask of the proposed method toperfusion MR images. Since perfusion images are of very low contrast, the pathological area, itmeans the tumor and a potential edema around it, has to be detected and segmented in anothertype of MR images.


Dvorak, P., Bartusek, K., & Kropatsch, W. (2013). Automated Segmentation of Brain Tumor Edema in FLAIR MRI Using Symmetry and Thresholding. In Proceedings of PIERS 2013 (pp. 936–939). http://hdl.handle.net/20.500.12708/54762