in a schematic illustration , fig1 shows an inventive examination and / or treatment device 1 having an ultrasound image acquisition device 2 as well as a control and processing device 3 that controls the operation of the ultrasound image acquisition device 2 and also undertakes the processing , editing and analysis of the image data . a set of 2d ultrasound images of an examination region — the heart of a patient 4 in this case — that are forwarded to the control and processing device 3 , are acquired with the ultrasound device 2 . in the illustrated example , the acquisition of the image data representing 2d ultrasound images ensues with triggering by an ecg 6 that is recorded in parallel , since the examination region 15 is a rhythmically moving organ , namely the heart . the ecg data are likewise forwarded to the control and processing device 3 . a position sensor 8 with which the spatial position of the ultrasound acquisition device 2 , and thus the respective spatial position of each acquired 2d ultrasound image can be identified , is also provided at the ultrasound acquisition device 2 . a suitable position detection system 16 is used for this purpose . the position data are likewise stored together with the 2d ultrasound images 5 . a preoperatively acquired 3d image dataset 7 of the examination region 15 is also present in the control and processing device 3 . this can be a computed tomography dataset , a magnetic resonance dataset or a 3d angiography image dataset . since this dataset was acquired preoperatively , i . e . at an arbitrary time before the current treatment , there is the possibility that it does not show the examination region in conformity with the current anatomical conditions . in order nonetheless to be able to employ this high - resolution 3d image dataset for producing a 3d reconstruction image in the context of a subsequent examination or treatment , it is necessary that it be updated , i . e . to adapt it to the current anatomical conditions . the updating of the 3d image dataset can ensue in two ways . a first way is to directly employ the 2d ultrasound images 5 , that are registered with a known spatial position with respect to the coordinate system of the 3d ultrasound image dataset . as an alternative , a 3d ultrasound image dataset 9 can be generated on the basis of the 2d ultrasound images 5 and utilized for the updating . this shall be discussed with reference to fig2 and 3 . a number of steps in accordance with the invention are schematically indicated as blocks in the control and processing device 3 . after the 3d image dataset has been updated in step 10 , the production of a 3d reconstruction image ensues in step 11 . as illustrated by step 12 ( only shown with broken lines ), there is also the possibility of mixing an instrument introduced into the examination region 3 into this 3d reconstruction image . this can ensue using the 2d ultrasound images that may possibly show this instrument . its position is detected ; as a result of the registration of the 2d ultrasound images 5 relative to the 3d image dataset , and the detected position and orientation are mixed into the 3d volume image with accurate position and orientation . of course , there is also the possibility of employing other two - dimensional images , for example x - ray fluoroscopic images , that show the instrument in the examination volume instead of the 2d ultrasound images . the 3d reconstruction image is subsequently presented at a monitor 13 with a representation of the instrument . fig2 shows the updating using a 3d ultrasound image dataset . this 3d ultrasound image dataset 9 — like the 3d image dataset 7 — is presented in the form of a volume . the respective volumes are subdivided into a number of small partial volumes , referred to as voxels . four voxels 7 a , 7 b , 7 c and 7 d are shown in the 3d image dataset 7 ; four corresponding voxels 9 a , 9 b , 9 c and 9 d are shown in the 3d ultrasound image dataset 9 . for the deformation and updating of the 3d image dataset 7 , the individual voxels are compared to one another and a determination is made as to whether the voxels of the 3d image dataset 7 agree with the corresponding voxels of the 3d ultrasound image dataset 9 . in the illustrated example , the voxels 7 a , 7 b , 7 c and the voxels 9 a , 9 b , 9 c coincide , i . e . there is an image data match . the voxel 7 d , which has been selected merely as an example , cannot be mapped onto the voxel 9 d with exact orientation and position . for the updating , a rigid registration of this voxel and of course of every other unmatched voxel , now ensues by translation and / or rotation of the respective voxel until it fits with the respective comparison voxel in the 3d ultrasound image dataset . the voxel 7 d is translationally or rotationally modified until it can be mapped congruently onto the voxel 9 d . a determination of the deformation of updating parameters ensues from this modification . when the corresponding deformation parameters have been identified for every non - matching voxel , then the actual updating of the 3d image dataset 7 ensues , i . e . it is modified dependent on the acquired updating requirements . the acquisition of differences , if any , within the voxels ensues by an analysis of the respective grayscale values . fig3 shows the updating using a 2d ultrasound image a schematic illustration . the 3d image dataset 7 also is shown in fig3 in the form of a three - dimensional cube . a 2d ultrasound image 5 is then mixed into this 3d image dataset 7 with exact position and orientation . as described , the exact spatial position of the 2d ultrasound image 5 in the 3d volume is known because of the acquisition of the spatial lay of a 2d ultrasound image 5 using the position sensor 5 and due to the registration of the 2d ultrasound image 5 with the coordinate system of the 3d image dataset 7 , so that this mixing can ensue . a check is also made , for example via a grayscale analysis , as to how the examination region that is shown in the tomogram plane of the 3d image dataset 7 and the examination region as shown in the 2d ultrasound image 5 coincide relative to one another . the tomogram plane from the 3d image dataset 7 is shown at the left in the illustrated example , the 2d ultrasound image 5 shown next to it , being mixed in over it or into it . the examination region is shown idealized as a circle in the 3d tomogram plane ( at the left ), whereas it is oval in the 2d ultrasound image that indicates the current anatomical conditions . the determination of the deformation or updating parameters now ensues such , for example via a suitable grayscale analysis or an edge detection algorithm , which describe how the presentation of the examination region shown in the 3d plane of section image 14 is to be shifted or deformed until it coincides with the presentation shown in the 2d ultrasound image 5 . this mixing and determination of the deformation parameters ensues until an updating of the complete 3d image dataset 7 is possible . although modifications and changes may be suggested by those skilled in the art , it is the intention of the inventors to embody within the patent warranted hereon all changes and modifications as reasonably and properly come within the scope of their contribution to the art .
in a method and apparatus for the three - dimensional presentation of an examination region of a patient in the form of a 3d reconstruction image , a preoperatively acquired 3d image dataset of the examination region is employed in a medical procedure , datasets representing a number of 2d ultrasound images of the examination region are acquired , the preoperative 3d image dataset is updated using the datasets representing 2d ultrasound images , and the 3d reconstruction image is generated on the basis of the updated 3d image dataset .