| Multi-feature statistical nonrigid registration using high-dimensional generalized information measures. | |
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MedLine Citation:
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PMID: 22003658 Owner: NLM Status: In-Process |
Abstract/OtherAbstract:
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Nonrigid image registration methods based on the optimization of information-theoretic measures provide versatile solutions for robustly aligning mono-modal data with nonlinear variations and multi-modal data in radiology. Whereas mutual information and its variations arise as a first choice, generalized information measures offer relevant alternatives in specific clinical contexts, Their usual application setting is the alignement of image pairs by statistically matching scalar random variables (generally, greylevel distributions), handled via their probability densities. In this paper, we address the issue of estimating and optimizing generalized information measures over high-dimensional state spaces to derive multi-feature statistical nonrigid registration models. Specifically, we introduce novel consistent and asymptotically unbiaised kappa nearest neighbors estimators of alpha-informations, and study their variational optimization over finite and infinite dimensional smooth transform spaces. The resulting theoretical framework provides a well-posed and computationally efficient alternative to entropic graph techniques. Its performances are assessed on two cardiological applications: measuring myocardial deformations in tagged MRI, and compensating cardio-thoracic motions in perfusion MRI. |
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Authors:
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Sameh Hamrouni; Nicolas Rougon; Françoise Prêteux |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Volume: 14 ISSN: - ISO Abbreviation: Med Image Comput Comput Assist Interv Publication Date: 2011 |
Date Detail:
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Created Date: 2011-10-18 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101249582 Medline TA: Med Image Comput Comput Assist Interv Country: Germany |
Other Details:
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Languages: eng Pagination: 524-31 Citation Subset: IM |
Affiliation:
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ARTEMIS Department, CNRS UMR 8145 - TELECOM SudParis, Evry, France. Sameh.Hamrouni@it-sudparis.eu |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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