Automatic shape based deformable registration of multiphase contrast enhanced liver CT volumes

The detection and assessment of many hepatic diseases is based on examination of multiphase liver CT volumes. Since phases contain complementary information, registration enables the radiologist to fuse the needed information for diagnosis or operation planning. This work presents a novel multi-stage approach for automatic registration of the liver in contrast enhanced CT volumes. Unlike other methods, our approach is based on automatic pre-segmentation of the liver in the different phases. Using the resulting shape information the volumes are coarsely registered using a landmark-based registration. Subsequently, deformations caused by the patient's breathing are compensated by an elastic Demons algorithm with a boundary distance based speed function. This allows for a high accuracy natural deformation without having to rely on error-prone extraction and matching of the liver's internal structure in complementary phases. Furthermore, since shape information is given, surrounding structures can be omitted which significantly speeds up registration. We evaluated our method using 22 CT volumes from 11 patients. The matching quality of outer shape and internal structures was validated by radiology experts. The high quality results of our approach suggest its applicability in clinical practice.