DATA FUSION IN MEDICAL IMAGING - MERGING MULTIMODAL AND MULTIPATIENT IMAGES, IDENTIFICATION OF STRUCTURES AND 3D DISPLAY ASPECTS

Data fusion in medical imaging can be seen into two ways (i) multisens ors fusion of anatomical and functional information and (ii) interpati ent data fusion by means of warping models. These two aspects set the methodological framework necessary to perform anatomical modelling esp ecially when concerning the modelling of brain structures. The major r elevance of the work presented here concerns the interpretation of mul timodal 3D neuro-anatomical data bases. Three types of data fusion pro blems are considered in this paper. The first one concerns the problem of data combination which includes multimodal registration (multisens or fusion applied to CT, MRI, DSA, PET, SPECT, or MEG). In particular, the problem of warping patient data to an anatomical atlas is reviewe d and a solution is proposed. The second problem of data fusion addres sed in this paper is the identification of anatomical structures by me ans of image analysis methods. Two techniques have been developed. The first one deals with the analysis of image geometrical features to en d up with the determination of a fuzzy mask to label the structure of interest. The second technique consists of labelling major cerebral st ructures by means of statistical image features associated with relaxa tion techniques. Finally, the paper presents a review of up to date 3D display techniques with a special emphasis on volume rendering and 3D display of combined data.