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Image registration is used extensively in medical imaging. Visual assessment of its quality is time consuming and not necessarily accurate. Automatic estimation of registration accuracy is desired for many clinical applications. Current methods rely on learning a relationship between image features and registration error. In this paper we propose an unsupervised method for the detection of local registration...
Automated liver segmentation is problematic due to variations in liver shape / size and because the liver has a similar density distribution to surrounding structures. We propose a method that: 1) utilizes iteratively constructed probabilistic liver and rib cage atlases, 2) conducts the Gaussian distribution analysis to avoid incorrectly classifying the irrelevant surrounding tissues as `liver region'...
Contrast-enhanced multiphase liver CT is currently a standard of practice in hepatic imaging for medical diagnosis of liver diseases. The main contribution of this paper is an image registration method which finds an accurate alignment of arterial phase and portal venous phase liver CT images. The proposed method combines global rigid registration (affine) and local nonrigid deformable registration...
Patient specific 3D finite element models have been developed using 4DCT (3D + time) image data for 5 liver cancer patients. Each model consists of the liver, tumors, left and right kidneys, stomach, spleen and body. Breathing motion of the liver, spleen and body is found and applied as displacement boundary conditions in the model. Sliding of the liver relative to the surrounding tissues is modeled...
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