Method, tomography apparatus and software product for evaluation of time-varying diagnostic procedures

A tomography apparatus comprising:

• a magnetic resonance scanner, adapted to receive an examination subject for obtaining image data in a series of exposures in a time sequence from the examination subject, said image data including a first image dataset representing exposures in said sequence obtained from said examination subject before an occurrence of a diagnostically relevant event associated with the examination subject, and including a second image dataset representing exposures in said sequence obtained at or after the occurrence of said diagnostically relevant event;
• and
• an image processor supplied with said image data for making a first correction to said image data by displacing contents of the respective exposures represented by said image data to cause a position of said examination subject in the respective exposures to substantially coincide, thereby obtaining a corrected first image dataset and a corrected second image dataset, and for making a second correction to said image data by forming an average image from said corrected first image dataset, and normalizing all exposures in said corrected first image dataset and said corrected second image dataset, image element-by-image element, to said average image, thereby obtaining normalized, corrected first image data, and making a third correction to said image data by identifying a value of at least one image element in a structurally uniform image region of an exposure in said normalized, corrected first image dataset, and subtracting said value of said at least one image element from respective values of each image element in said region in said first image dataset and said second image dataset.

A computer software product stored in a memory accessible by a processor for correcting image data in a series of exposures obtained in a time sequence from an examination subject with a tomography apparatus, said image data including a first image dataset representing exposures in said sequence obtained from said examination subject before an occurrence of a diagnostically relevant event associated with said examination subject, and including a second image dataset representing exposures in said sequence obtained at or after the occurrence of said diagnostically relevant event, said computer software product programming said processor to:

• make a first correction to said image data by displacing contents of the respective exposures represented by said image data to cause a position of said examination subject in the respective exposures to substantially coincide, thereby obtaining a corrected first image dataset and a corrected second image dataset;
• make a second correction to said image data by forming an average image from said corrected first image dataset, and normalizing all exposures in said corrected first image dataset and said corrected second image dataset, image element-by-image element, to said average image, thereby obtaining normalized, corrected first image data;
• and
• make a third correction to said image data by identifying a value of at least one image element in a structurally uniform image region of an exposure in said normalized, corrected first image dataset, and subtracting said value of said at least one image element from respective values of each image element in said region in said first image dataset and said second image dataset.