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Automatic image registration of three-dimensional images of the head of cats and dogs by use of maximization of mutual information
Authors:Böttcher Peter  Maierl Johann  Hecht Silke  Matis Ulrike  Liebich Hans-Georg
Institution:Department of Small Animal Surgery, Faculty of Veterinary Medicine, Ludwig-Maximilians-University, Munich, Germany.
Abstract:OBJECTIVE: To validate mutual information criterion as a ready-to-use technique for automated alignment (ie, registration) of 3-dimensional (3-D) multimodal image data of the head of cats and dogs. SAMPLE POPULATION: Corresponding 3-D magnetic resonance imaging (MRI) and computed tomography (CT) brain scans of a 6-month-old Doberman Pinscher with a brain cyst; CT images of the head of a European shorthair cat with a meningioma before and immediately, 3, and 6 months after surgical resection; and CT and corresponding stacked anatomic cryosection images of the entire head of a 2-year-old sexually intact female Beagle. PROCEDURE: All images were matched retrospectively by use of an in-house computer program developed on the basis of a mutual information image registration algorithm. Accuracy of the resulting registrations was evaluated by visual inspection. RESULTS: All registrations were judged to be highly accurate. Additional manual corrections were not necessary. CONCLUSIONS AND CLINICAL RELEVANCE: Mutual information registration criterion can by applied to 3-D multimodal head images of cats and dogs for full automatic rigid-body image registration. The combination of such aligned images would considerably facilitate efforts of veterinary clinicians as indicated by its widespread use in brain surgery and radiation therapy of humans.
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