Contrast-enhanced multiphase liver CT is currently a standard of practice in hepatic imaging for medical diagnosis of liver diseases. We presented a novel image registration method for liver CT multiphase images. Firstly, a biomechanical model is proposed to describe the procedure of image registration, and expressed by an energy function. Then the numerical approximation of the energy function based on three dimensional Level-Set method is implemented which is accelerated by Compute Unified Device Architecture (CUDA) to make sure that our method can meet the clinical real-time requirement. Experiments show that our method can accurately register liver CT multiphase images. And compared with other algorithm, our method is much faster, and higher the image resolution is, bigger the speed-up ration is. Multiphase liver CT is widely used to detect and characterize liver lesions as different types of tumors enhance differently during each phase. The four phases are precontrast phase, arterial phase, portal venous phase, and delayed phase. Precontrast liver scans are used to detect calcifications, visualize hemorrhage from trauma, and demonstrate hyper vascular lesions which appear hypodense compared to the surrounding liver parenchyma. The arterial phase of scanning is performed approximately 30 seconds after the contrast injection is initiated and is most accurately determined by using bolus tracking software to monitor the level of contrast enhancement in the aorta and automatically triggering the scan when it reaches a pre determined level of enhancement (eg 120HU). Hyper vascular lesions enhance during the arterial phase and appear hyperdense. Arterial phase images are also used for pre operative evaluation of the arterial vasculature through the use of maximum intensity projection (MIP) and 3D reconstructions. The portal venous phase is performed 70-90 seconds post contrast and hypo vascular lesions appear hypodense and hyper vascular lesions appear isodense (same density as surrounding liver).The delayed phase is performed 5-10 minutes post contrast and is used to further characterize lesions. Clinicians need to make diagnosis based on the medical information from liver CT multiphase images, especially from arterial phase and portal venous phase. However, during the image data acquisition, tissues and organs in liver CT images from different phase may have subtle differences due to breath, heartbeat, subconscious physical movement, and so on, which may mislead clinicians and increase difficulties of making diagnosis. In order to solve this problem, image registration algorithms between multiphase images are necessary, which can enable the radiologist to fuse the needed information for diagnosis or operation planning. Zhai K and colleagues presented an image registration method which finds an accurate alignment of arterial phase and portal venous phase liver CT images(1), they combined global rigid registration (affine) and local nonrigid deformable registration (B-spline) in a manner of alternative iterations, and extended traditional two-step registration to iterative multi-step registration. Cao Y and colleagues proposed a feature-based non-rigid registration approach for multiphase liver CT images(2), this algorithm is comprised of four steps: firstly, extracting corners and edges from referenced and floating images using Harris corner detector; secondly, using joint descriptor of SIFT and shape context to describe features; thirdly, segmenting the entire abdominal region into two sub-regions and matching the sub-regions respectively; finally, using thin-plate splines to model deformation field between correspondences. Erdt M and colleagues firstly make a pre-segmentation of the liver in the different phase, then use the resulting shape information of the volumes to coarsely register by
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