Classification of XXXX in magnetic resonance images using spectral and fractal analysis.

@entity1 @entity174 @entity5 @entity170 @entity3814 @entity130
UNASSIGNED: Fractures with partial collapse of vertebral bodies are generically referred to as " @entity3814 " or VCFs. VCFs can have different etiologies comprising @entity130 , bone failure related to @entity170 , or @entity5 affecting bone. VCFs related to @entity170 (benign @entity174 ) and to cancer ( @entity174 ) are commonly found in the elderly population. In the clinical setting, the differentiation between benign and @entity174 is complex and difficult. This paper presents a study aimed at developing a system for computer-aided diagnosis to help in the differentiation between malignant and benign VCFs in magnetic resonance imaging (MRI). We used T1-weighted MRI of the lumbar spine in the sagittal plane. Images from 47 consecutive @entity1 (31 @entity1 , 16 @entity1 , mean age 63 years) were studied, including 19 @entity174 and 54 benign @entity174 . Spectral and fractal features were extracted from manually segmented images of 73 vertebral bodies with VCFs. The classification of malignant vs. benign VCFs was performed using the k-nearest neighbor classifier with the Euclidean distance. Results obtained show that combinations of features derived from Fourier and wavelet transforms, together with the fractal dimension, were able to obtain correct classification rate up to 94.7% with area under the receiver operating characteristic curve up to 0.95.
