Title :
Automated Classification of Bone and Air Volumes for Hybrid PET-MRI Brain Imaging
Author :
Chan, Sze-Liang Stanley ; Gal, Yaniv ; Jeffree, Rosalind L. ; Fay, Marcelo ; Thomas, Paul ; Crozier, Stuart ; Zhengyi Yang
Author_Institution :
Univ. of Queensland, Brisbane, QLD, Australia
Abstract :
In clinically applicable structural magnetic resonance images (MRI), bone and air have similarly low signal intensity, making the differentiation between them a very challenging task. MRI-based bone/air segmentation, however, is a critical step in some emerging applications, such as skull atlas building, MRI-based attenuation correction for Positron Emission Tomography (PET), and MRI-based radiotherapy planning. In view of the availability of hybrid PET-MRI machines, we propose a voxel-wise classification method for bone/air segmentation. The method is based on random forest theory and features extracted from structural MRI and attenuation uncorrected PET. The Dice Similarity Score (DSC) score between the segmentation result and the ´ground truth´ obtained by thresholding Computed Tomography images was calculated for validation. Images from 10 subjects were used for validation, achieving a DSC of 0.83±0.08 and 0.98±0.01 for air and bone, respectively. The results suggest that structural MRI and uncorrected PET can be used to reliably differentiate between air and bone.
Keywords :
biomedical MRI; bone; feature extraction; image classification; image segmentation; medical image processing; positron emission tomography; DSC; MRI-based attenuation correction; MRI-based bone-air segmentation; MRI-based radiotherapy planning; air volume automated classification; bone automated classification; computed tomography images; dice similarity score; feature extraction; hybrid PET-MRI brain imaging; positron emission tomography; random forest theory; signal intensity; skull atlas building; structural magnetic resonance images; voxel-wise classification method; Attenuation; Bones; Computed tomography; Feature extraction; Image segmentation; Magnetic resonance imaging; Positron emission tomography;
Conference_Titel :
Digital Image Computing: Techniques and Applications (DICTA), 2013 International Conference on
Conference_Location :
Hobart, TAS
DOI :
10.1109/DICTA.2013.6691483