  Ultrasound (US) is the most commonly used liver imaging modality worldwide.
Due to its low cost, it is increasingly used in the follow-up of cancer
patients with metastases localized in the liver. In this contribution, we
present the results of an interactive segmentation approach for liver
metastases in US acquisitions. A (semi-) automatic segmentation is still very
challenging because of the low image quality and the low contrast between the
metastasis and the surrounding liver tissue. Thus, the state of the art in
clinical practice is still manual measurement and outlining of the metastases
in the US images. We tackle the problem by providing an interactive
segmentation approach providing real-time feedback of the segmentation results.
The approach has been evaluated with typical US acquisitions from the clinical
routine, and the datasets consisted of pancreatic cancer metastases. Even for
difficult cases, satisfying segmentations results could be achieved because of
the interactive real-time behavior of the approach. In total, 40 clinical
images have been evaluated with our method by comparing the results against
manual ground truth segmentations. This evaluation yielded to an average Dice
Score of 85% and an average Hausdorff Distance of 13 pixels.
