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Abstract #0828

Automatic Lesion Detection in White & Grey Matter Using T1-Weighted and FLAIR Images

Javier Gonzlez-Zabaleta1, Norberto Malpica1, Ana Ramos2, Juan lvarez-Linera3, Juan Antonio Hernndez-Tamames1

1Neuroimaging lab., Center for Biomedical Technology, Universidad Politcnica de Madrid and Universidad Rey Juan Carlos, Pozuelo de Alarcn, Madrid, Spain; 2Hospital 12 de Octubre, Madrid, Spain; 3Hospital Ruber Internacional, Madrid, Spain

Cortical lesions in multiple sclerosis are characterized by simultaneous hiperintensity in FLAIR images and hypointensity in T1 images. We have developed a method for automatic lesion detection that includes tissue segmentation correction, lesion detection and quantification. We have evaluated the technique in a study on Multiple Sclerosis, including 21 controls and 15 patients. All subjects were correctly classified with our method. All the algorithms have been included in a plugin for 3D Slicer.