When processing medical image data, it is frequently necessary to compare two or more image data records for a patient with one another which have been measured in the same period on different imaging modalities, on the same imaging modality in the same period but with different parameters, or on the same imaging modality in different periods. By way of example, this relates to applications in which a patient has been successively examined both using PET (Positron Emission Tomography) and using CT (Computer Tomography), which means that both PET and CT image data records are available. Other examples are different pervasions of contrast agent in the organs in the case of image recording using CT, in which case at least two image data records with different contrast agent distributions in the organs are obtained, or follow-up examinations where the patient is examined at a relatively long interval time using not necessarily identical recording parameters.
In all cases, it is desirable to compare the different image data records as well as possible. In principle, comparison is possible by fusing two image data records, by parallel visualization in the case of almost identical anatomies or by combining an anatomical image and an image of physiological processes (as in the case of PET and CT image data) in the data records or by navigating to a position in the second image data record which is selected in a first image data record. However, the image data records will generally not contain any identical anatomies. Changes in the position of the organs, changes in the patient position for the image recording or weight changes in the patient between recordings mean that simple association on the basis of coordinates is not possible.
To avoid these problems, registration methods are known which use a rigid or nonrigid registration technique. These first of all involve searching the image data records for identical structures, for example. Next, these identical structures are taken as a basis for calculating transformation matrices which map every voxel in the structures of one data record onto a voxel in the corresponding structures in the second data record. The transformations are then generalized for the whole data record.
When there are more than two image data records, the image data records are at present respectively registered in pairs. With large volumes of data, this results in long waiting times for the user on account of the high computation complexity for registration. Thus, in the case of a polyphase examination of the liver, for example, a native CT scan, i.e. a scan without contrast agent, is first of all performed. Next, the pervasion of the contrast agent in the liver artery, in the portal vein and in the liver parenchyma is examined. This results in four image data records and hence six pairs which are respectively registered with one another.