A computer-implemented method for automatic detection on clinical relevance of images of an anatomical situation provided by an imaging device, the method comprising: taking a first image of the anatomical situation; taking a subsequent second image of the anatomical situation; comparing the first image and the second image and determining a difference between the first image and the second image; wherein comparing and determining a difference of the first image and the second image includes separating each of the first image and the second image into corresponding image blocks each comprising a plurality of pixel, and comparing at least one of the corresponding image blocks of the first and second image, determining whether the difference between the first image and the second image comprises at least one of a local type difference and a global type difference, wherein the local type difference is a local difference of the first image and the second image and wherein the global type difference is a global difference between the first image and the second image, and determining whether the second image has clinical relevance, characterized in that, determining whether the second image has clinical relevance comprises determining if the global difference of the first image and the second image exceeds a second predetermined threshold, in case the global difference is below the second predetermined threshold, determining whether the second image has clinical relevance comprises determining if the local difference of the first image and the second image exceeds a first predetermined threshold, wherein the local type difference is detected if a local difference of a SE:BH particular image block of the first image and a corresponding image block of the second image exceeds a first predetermined threshold, and wherein the global type difference is detected if a global difference of entire image blocks of the first image and a corresponding image blocks of the second image exceeds a second predetermined threshold, wherein the second threshold is larger than the first threshold. taking a first image of the anatomical situation; taking a subsequent second image of the anatomical situation; comparing the first image and the second image and determining a difference between the first image and the second image; wherein comparing and determining a difference of the first image and the second image includes separating each of the first image and the second image into corresponding image blocks each comprising a plurality of pixel, and comparing at least one of the corresponding image blocks of the first and second image, determining whether the difference between the first image and the second image comprises at least one of a local type difference and a global type difference, wherein the local type difference is a local difference of the first image and the second image and wherein the global type difference is a global difference between the first image and the second image, and determining whether the second image has clinical relevance, characterized in that, determining whether the second image has clinical relevance comprises determining if the global difference of the first image and the second image exceeds a second predetermined threshold, in case the global difference is below the second predetermined threshold, determining whether the second image has clinical relevance comprises determining if the local difference of the first image and the second image exceeds a first predetermined threshold, wherein the local type difference is detected if a local difference of a SE:BH particular image block of the first image and a corresponding image block of the second image exceeds a first predetermined threshold, and wherein the global type difference is detected if a global difference of entire image blocks of the first image and a corresponding image blocks of the second image exceeds a second predetermined threshold, wherein the second threshold is larger than the first threshold.