Distance transformations in digital images
Computer Vision, Graphics, and Image Processing
Generalized Parallel-Perspective Stereo Mosaics from Airborne Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph Partitioning Active Contours (GPAC) for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image registration by "Super-curves"
IEEE Transactions on Image Processing
High-throughput analysis of multispectral images of breast cancer tissue
IEEE Transactions on Image Processing
Image registration using the Walsh transform
IEEE Transactions on Image Processing
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This paper presents a novel approach for registration of 3D images based on optimal free-form rigid transformation. A proposal consists in semiautomatic image segmentation reconstructing 3D object surfaces in medical images. The proposed extraction technique employs gradients in sequences of 3D medical images to attract a deformable surface model by using imaging planes that correspond to multiple locations of feature points in space, instead of detecting contours on each imaging plane in isolation. Feature points are used as a reference before and after a deformation. An issue concerning this relation is difficult and deserves attention to develop a methodology to find the optimal number of points that gives the best estimates and does not sacrifice computational speed. After generating a representation for each of two 3D objects, we find the best similarity transformation that represents the object deformation between them. The proposed approach has been tested using different imaging modalities by morphing data from Histology sections to match MRI of carotid artery.