| Abstract |
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Image reconstruction is an active research field, due to the increasing need for geometric 3D models in movie industry, games, virtual environments and in medical fields. 3D image reconstruction aims to arrive at the 3D model of an object, from its 2D images taken at different viewing angles. Medical images are multimodal, which includes MRI, CT scan image, PET and SPECT images. Of these, MRI and CT scan images of an organ when taken, is available as a stack of 2D images, taken at different angles. This 2D stack of images is used to get a 3D view of the organ of interest, to aid doctors in easier diagnosis. Existing 3D reconstruction techniques are voxel based techniques, which tries to reconstruct the 3D view based on the intensity value stored at each voxel location. These techniques don’t make use of the shape/depth information available in the 2D image stack. In this work, a 3D reconstruction technique for MRI/CT 2D image stack, based on Shapelets has been proposed. Here, the shape/depth information available in each 2D image in the image stack is manipulated to get a 3D reconstruction, which gives a more accurate 3D view of the organ of interest. Experimental results exhibit the efficiency of this proposed technique. |
