A method of localization of electrodes for monitoring bioelectric signals from the brain in patients suffering from neurodegenerative diseases, comprising: - a retrieving step concerning the retrieval of biomedical images in the form of MRI and CT scans from hospital RIS-PACS databases as Digital Imaging and Communications in Medicine (DICOM) format, and their conversion into two sets of volumetric images in a format such as Neuroimaging Informatics Technology Initiative (NIFTI) or Analyze (Mayo Foundation, Biomedical Imaging Resource, "Analyze 7.5 File Format"); - an interfacing step for establishing a connection to the clinical data of a patient whose biomedical images are being processed; and - a biomedical image processing step, comprising: - loading the two sets of volumetric MRI and CT images; - co-registering said two sets of images according to the Normalized Mutual Information; - application of Gaussian filters to said two sets of images to remove noise and artifacts; - MRI image segmentation by using the Unified Segmentation method; - extraction of electrodes from a volumetric CT image; - creation of the array of electrodes extracted with their respective spatial co-ordinates for further anatomical localization purposes; - creation of the patient's brain rendering by means of isosurface extraction technique; - projection of the extracted electrodes on the cortical rendering, characterized in that the extraction of electrodes from the volumetric CT image is done by automatic thresholding that is optimized by the user's setting of parameters including voxel intensity, size of the voxel mask obtained by the automatic thresholding, minimum and maximum distance between the electrodes, contrast and brightness. - a retrieving step concerning the retrieval of biomedical images in the form of MRI and CT scans from hospital RIS-PACS databases as Digital Imaging and Communications in Medicine (DICOM) format, and their conversion into two sets of volumetric images in a format such as Neuroimaging Informatics Technology Initiative (NIFTI) or Analyze (Mayo Foundation, Biomedical Imaging Resource, "Analyze 7.5 File Format"); - an interfacing step for establishing a connection to the clinical data of a patient whose biomedical images are being processed; and - a biomedical image processing step, comprising: - loading the two sets of volumetric MRI and CT images; - co-registering said two sets of images according to the Normalized Mutual Information; - application of Gaussian filters to said two sets of images to remove noise and artifacts; - MRI image segmentation by using the Unified Segmentation method; - extraction of electrodes from a volumetric CT image; - creation of the array of electrodes extracted with their respective spatial co-ordinates for further anatomical localization purposes; - creation of the patient's brain rendering by means of isosurface extraction technique; - projection of the extracted electrodes on the cortical rendering, characterized in that the extraction of electrodes from the volumetric CT image is done by automatic thresholding that is optimized by the user's setting of parameters including voxel intensity, size of the voxel mask obtained by the automatic thresholding, minimum and maximum distance between the electrodes, contrast and brightness. - loading the two sets of volumetric MRI and CT images; - co-registering said two sets of images according to the Normalized Mutual Information; - application of Gaussian filters to said two sets of images to remove noise and artifacts; - MRI image segmentation by using the Unified Segmentation method; - extraction of electrodes from a volumetric CT image; - creation of the array of electrodes extracted with their respective spatial co-ordinates for further anatomical localization purposes; - creation of the patient's brain rendering by means of isosurface extraction technique; - projection of the extracted electrodes on the cortical rendering, characterized in that the extraction of electrodes from the volumetric CT image is done by automatic thresholding that is optimized by the user's setting of parameters including voxel intensity, size of the voxel mask obtained by the automatic thresholding, minimum and maximum distance between the electrodes, contrast and brightness.