Meningioma and peritumoral edema segmentation of preoperative MRI brain scans

Abstract

This work focuses the attention on the segmentation of meningioma and peritumoral edema from multispectral brain MR imagery. Precise tumour and edema delineation and volume quantification from preoperative MRI data contribute to formulate surgical indications in elderly patients harbouring intracranial meningioma. The authors propose a fully automatic procedure based on the allied use of Graph Cut and support vector machine. The overall strategy combines the advantages of the image-based and machine learning techniques adopted, optimising the balancing between accuracy and stability/reproducibility of the results. Experimental results, obtained by processing in-house collected data, prove that the method is robust and oriented to the use in clinical practice.

Keywords:

• Magnetic resonance imaging
• brain tumour segmentation
• meningioma segmentation
• edema segmentation
• Graph Cut
• support vector machine