Title :
Classification of trabecular bone texture from MRI and CT scan images by multi resolution analysis
Author :
Khider, M. ; Taleb-Ahmed, A. ; Dubois, P. ; Haddad, Bassam
Author_Institution :
Valenciennes & Hainaut Cambresis Univ., Valenciennes
Abstract :
Although bone mineral density measurements constitute one of the main clinical indicators of osteoporosis, we know that bone fragility risk is also related to deteriorations of osseous architecture. Medical imaging constitutes one means to appreciate in vivo bone screen, what is particularly important in the follow up of the osteoporosis. This paper presents a method of bone textural MRI and CT scan classification, based on the use of multifractal analysis by the WTMM-2d method, we propose the choice of three features to realize these images classification: the Holder exponents average at the peaks of Legendre spectrums, the wavelet transform skeletons density by pixel, and variance of directions of gradients. The preliminary results of 40 images directly resulting from two medical imaging (MRI and CT scan), prove to be interesting since 90% of cases are well estimated, and two classes instantaneous clustering of the results (one healthy patient class and one osteoporotic patient class) quite separate.
Keywords :
biomedical MRI; biomineralisation; bone; computerised tomography; diseases; image classification; CT scan imaging; Holder exponents average; Legendre spectrum; MRI imaging; WTMM-2d method; bone fragility risk; bone mineral density; image classification; in vivo bone screen; multifractal analysis; multiresolution analysis; osseous architecture; osteoporosis; trabecular bone texture; wavelet transform skeletons density; Biomedical imaging; Cancellous bone; Computed tomography; Density measurement; Image analysis; Image resolution; Image texture analysis; Magnetic resonance imaging; Minerals; Osteoporosis; Algorithms; Artificial Intelligence; Bone and Bones; Cluster Analysis; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Osteoporosis; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
Print_ISBN :
978-1-4244-0787-3
DOI :
10.1109/IEMBS.2007.4353613