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Medical image registration based on random line sampling

One of the key aspects in 3D-image registration is the computation of the joint intensity histogram. We propose a new approach to compute this histogram using uniformly distributed random lines to sample stochastically the overlapping volume between two 3D-images. The intensity values are captured from the lines at evenly spaced positions, taking an initial random offset different for each line. This method provides us with an accurate, robust and fast mutual information-based registration. The interpolation effects are drastically reduced, due to the stochastic nature of the line generation, and the alignment process is also accelerated. The results obtained show a better performance of the introduced method than the classic computation of the joint histogram

IEEE

Author: Bardera i Reig, Antoni
Feixas Feixas, Miquel
Boada, Imma
Sbert, Mateu
Abstract: One of the key aspects in 3D-image registration is the computation of the joint intensity histogram. We propose a new approach to compute this histogram using uniformly distributed random lines to sample stochastically the overlapping volume between two 3D-images. The intensity values are captured from the lines at evenly spaced positions, taking an initial random offset different for each line. This method provides us with an accurate, robust and fast mutual information-based registration. The interpolation effects are drastically reduced, due to the stochastic nature of the line generation, and the alignment process is also accelerated. The results obtained show a better performance of the introduced method than the classic computation of the joint histogram
Document access: http://hdl.handle.net/2072/94956
Language: eng
Publisher: IEEE
Rights: Tots els drets reservats
Subject: Imatgeria mèdica -- Processament
Processos estocàstics
Imatgeria tridimensional en medicina
Imaging systems in medicine
Stochastic processes
Three-dimensional imaging in medicine
Title: Medical image registration based on random line sampling
Type: info:eu-repo/semantics/article
Repository: Recercat

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