the present application is a system and method for flexible fusion of two data sets representing three - dimensional densities of a physical properties . according to a preferred embodiment of the present application , two data sets , which both represent the same object , but were generated using different acquisition methods , are combined in such a way , that the advantages of a particular acquisition method can be of use for a data set that was acquired using a different radiological method . for sake of clarity , the present application is explained here with reference to a preferred embodiment employing two diagnostical radiological methods in particular , these two methods being three - dimensional rotational angiography ( 3dra ) on the one hand and computer tomography ( ct ) on the other hand . ct is typically used for visualization of low contrast soft tissue such as brain material , while 3dra is effectively used for visualization of high contrast artery / vessel structures . since 3dra and ct volumes provide complementary information to the clinical users , it is desirable to present this information to them as effectively as possible . referring to fig1 , using a computer tomography acquisition device ct , a data set corresponding to the three - dimensional spacial distribution of a physical property inside an examination volume is acquired . in the case of ct , the physical property is the attenuation coefficient with regard to x - rays . the same object , which in a clinical environment is usually a patient , undergoes a second acquisition , this time using a 3dra acquisition device 3dra . this technique relies on the same physical principle , namely measuring the attenuation coefficient distribution with regard to x - ray radiation , but differs from ct in the shape of the sensor and the acquisition geometry . in particular , 3dra employs a central projection onto a two - dimensional radiation detector , whereas ct uses substantially one - dimensional detector arrays . 3dra datasets generally do not contain absolute calibrated density values , due to insufficient calibration and reconstruction procedures . both acquired data sets are transmitted to a data receiving and processing unit dpu . the data receiving and processing unit dpu receives the two data sets as inputs and forwards them to several sub - units . with reference to the 3dra - generated data , the pre - processing unit prp eliminates unwanted artefacts inherent to the 3dra technique and improves the performance of downstream data processing units . the pre - processing unit prp can be incorporated with either the data receiving and processing unit dpu as depicted in fig1 or the 3dra acquisition device 3dra . the pre - processed 3dra data set is then transmitted to both , an artery / vessel segmentation unit aseg and a registration unit reg , charged with the registration of the ct data set and the 3dra data set . the other input for the registration unit reg is supplied with the data set generated by the ct acquisition device ct . the registration unit ensures , that both data sets are placed in a common co - ordinate system in such a manner , that an object contained in both data sets will be located in the same location regarding each data set . in the described embodiment , the 3dra - generated data set remains constant , while the ct - generated data set is shifted , scaled and rotated in such way , that a maximum of congruence in position , size and orientation is achieved . the accordingly altered ct - generated data set is transmitted to two destinations , one of which is a unit for rendering a transparent volume slice sren , and the other is a unit for bone / skull segmentation sseg . the latter proceeds to segmenting skull / bone information from the ct - generated data set , the result of which will be made available to a 3d masking unit msk . another input of this unit is provided by the artery segmentation unit aseg , that has segmented artery / vessel information from the 3dra - generated data set . due to the similar acquisition characteristics of artery / vessel tissue and the skull in the case of 3dra , the segmented artery / vessel information still contains a considerable quantity of voxels corresponding to the skull and bones . the 3d masking unit msk merges the two data sets provided by unit sseg and unit aseg , respectively , in order to blind out any skull information in the 3dra - generated data set . in particular , the segmented skull / bone information extracted from the ct - generated data set is used as a mask , applied to the segmented artery / vessel information . notice that , due to the different voxel densities , straightforward subtraction will not work in general . an interpolation method , taking into account several voxels of the masking information for one voxel of the evaluation data set , or vice versa , depending on the location in the scanned volume of the voxels , has to be considered , instead . the resulting information contains by and large only the desired artery / vessel information . in order to be able to display this information in an efficient way to clinical users , the data set has to be passed to a 3d rendering unit aren , being a part of the visual output means vis . based on a user selected viewpoint , illumination , the data set to be displayed and other parameters , a view of the 3d data is generated by 3d rendering aren by a projection onto 2d space . this 2d - projection is suited to be displayed by a frame buffer display fbd . if the clinical user is further interested in the condition of the surrounding tissue in the vicinity of an observed blood vessel , e . g . to be able to evaluate any correlated symptoms , the system reverts to the ct - generated data , which has better capabilities in this domain . to this end , the same data feeding the skull / bone segmentation unit sseg is also applied to a unit for transparent volume slice rendering sren . since large volumes are difficult for a user , even if well trained , to grasp , it is preferred , that the additionally displayed ct data is rendered in form of a slice or another simple three - dimensional geometric shape . control of the position , orientation , size , transparency and other properties of the slice is performed by a volume - slice control unit vsc , either automatically or by interpreting commands issued by the user . by rendering the slice or the equivalent geometrical shape transparent , the problem , that the ct image covers a lot of the arterial / vessel information is resolved . however , transparent rendering will heavily influence the contrast of the ct information , which is clinically unacceptable . a remedy is to add non transparent , multi - planar reformatting ( mpr ) rendering of the top or bottom planes to the transparent rendered volume slice , in order to get the required high contrast in these planes . this is achieved by a second unit for rendering , the cap mpr rendering unit cren . depending on the view angle , either the top or the bottom plane is rendered non transparent . the operation of the visual output means vis is controlled by a viewing control unit vc . via this means , the user can interact with the system for modifying view point , zoom etc . the user can further place a virtual probe in a specific location , causing the means for visualization to represent the surrounding tissue in the vicinity of the probe location . by letting the clinical users modify the position and / or orientation of the ct slices , relative to the viewing of the artery / vessel structures , they will have a flexible and clear view of the pathologies at hand . for example , the probe can be placed on an artery vessel by a clinical user , who has an insight on the ct information in the plane orthogonal to the direction of flow . now with reference to fig2 , the result of artery / vessel information based solely on 3dra data is shown . it becomes apparent , that besides the desired artery / vessel information considerable areas corresponding to the skull are contained in the displayed scan . referring now to fig3 , the result of masking the segmented artery / vessel data set shown in fig2 with the data set containing the segmented skull , based on the ct image , is represented . it becomes apparent , that a considerable improvement is obtained over segmentation based solely on 3dra - generated data . now with reference to fig4 , a combined 3dra - ct image is shown , in which a slice containing ct data , and correspondingly representing the skull and soft tissue , is rendered transparent . the bottom plane of this slice , however , is rendered non transparent , as to make more clearly apparent soft tissue . since a clinical user can adjust the viewpoint , the fact , that some of the 3dra data is temporarily obscured by the non transparent plane , can easily be dealt with by redefining another viewpoint . now with reference to fig5 , an example of a region of registration is depicted . in order for the registration to yield high quality results , it is not necessary , that the entire volume is evaluated . it must rather be guaranteed , that unequivocal points of reference can be determined and located in both data sets . these points of reference can either be anatomical landmarks or artificial markers , that are applied to the patient . the location of the points of reference can be determined manually or automatically . exemplary , fig5 shows a patient &# 39 ; s head 510 . a simple region to be used for registration is represented by the tetrahedron 520 , where each of its four vertices 522 , 524 , 526 , 528 corresponds to an anatomical landmark or a marker . of course , other shapes can be used as well . in another embodiment , the skull , which usually clearly distinguishable in both kinds of images , can serve as a limiting boundary for the registration region , which generalizes the concept of anatomical landmarks . in another preferred embodiment , a clinical user can put a probe on an artery / vessel and have an insight on the ct information on the plane orthogonal to the direction of flow . in another preferred embodiment , the user can , by specifying a begin and end probe , trace through a path being able to see the sequence of ct - slices in the direction of flow . in a further embodiment , the order of certain operations could be changed . for example , the artery / vessel segmentation could benefit from previously executed masking of skullbone regions from the 3dra - generated data set using the ct data . in terms of fig1 , this would mean , that blocs aseg and msk would be rearranged in the reverser order . furthermore , several units can be combined into one unit , such as a processor . the application is not limited to the mentioned radiological methods , but extends to other methods that can be combined in the described fashion as well . the application is of course not limited to the described or shown embodiments , but generally extends to any embodiment , which falls within the scope of the appended claims as seen in light of the foregoing description and drawings . while a particular feature of the application may have been described above with respect to only one of the illustrated embodiments , such features may be combined with one or more features of other embodiments , as may be desired and advantageous for any given particular application . from the above description of the application , those skilled in the art will perceive improvements , changes and modifications . such improvements , changes and modifications within the skill of the art are intended to be covered by the appended claims . any reference signs in the claims do not limit the scope of the application . the term “ comprising ” is to be understood as not excluding other elements or steps and the term “ a ” or “ an ” does not exclude a plurality .
one of two data sets , originating from two different radiological methods is processed to generate interim results , yielded by an operation on one of the data sets . the interim results are used to modify the other data set . different imaging capabilities of the employed radiological methods promote a particular task , e . g . the segmentation of a given type of tissue . when the combined data of both methods is displayed , clinical users benefit from the complementary information . care is taken , that only relevant information is presented to the user , as to avoid irrelevant data obscuring any data of interest . therefore , the data to be displayed is filtered based on content , e . g . the type of tissue , and on location . three - dimensional computer tomography and three - dimensional rotational angiography are particularly applicable radiological methods .