Open AccessTHE ROLE OF TECHNOLOGY IN THE INTEGRATION BETWEEN BIOMEDICAL SIGNALS AND BIOIMAGING
Author(s) -
Sergio Cerutti,
Anna Maria Bianchi,
Giovanna Rizzo
Publication year - 2011
Publication title -
incontri di studio
Language(s) - English
Resource type - Journals
eISSN - 2384-9878
pISSN - 2279-5251
DOI - 10.4081/incontri.2002.6
Subject(s) - computer science , positron emission tomography , neuroimaging , neuroscience , magnetic resonance imaging , modality (human–computer interaction) , artificial intelligence , signal (programming language) , functional integration , human brain , medical physics , pattern recognition (psychology) , medicine , radiology , biology , mathematical analysis , mathematics , programming language , integral equation
In the last few years the tremendous developments in biomedical technologies made available advanced instrumentation and new data processing techniques able to provide new knowledge on morphology and functional features of internal organs by a multiscale approach. Several techniques are currently available for the examination of the brain under normal and pathological conditions. Magnetic Resonance Imaging (MRI) and x-ray Computed Tomography (CT) supply information about the brain structure. Emission Tomography (PET, SPET) permits the investigation of the functional activity of the brain by measurements of blood flow, metabolism and receptor distribution. The localization of the bio-electric sources of the brain’s electric and magnetic fields at the scalp surface can be achieved by EEG and MEG signal analysis. Correlation of such different information can support the comprehension of the human brain in patho-physiological conditions, since the integration of multimodal information allows us to overcome intrinsic limitations and to enhance the specific potential of each technique. To help forming a correct interpretation of the relation among the different modalities, a unique spatial reference system is defined, into which one must represent images and signals relative to the same subject. Integration of imaging and signal techniques provides an accurate description of cerebral functions with high spatial and temporal resolution, thus representing a powerful probe for brain investigation both in basic and clinical neuroscience.