Tuning and comparing spatial normalization methods
| Autor: | Steven M. Robbins, D. Louis Collins, Alan C. Evans, Sue Whitesides |
|---|---|
| Rok vydání: | 2004 |
| Předmět: |
Surface (mathematics)
Computer science Image registration Value (computer science) Health Informatics Brain mapping Imaging Three-Dimensional Image Processing Computer-Assisted Humans Radiology Nuclear Medicine and imaging Computer vision Brain Mapping Radiological and Ultrasound Technology business.industry Process (computing) Brain Pattern recognition Magnetic Resonance Imaging Computer Graphics and Computer-Aided Design Range (mathematics) Spatial normalization Key (cryptography) Computer Vision and Pattern Recognition Artificial intelligence business Algorithms |
| Zdroj: | Medical Image Analysis. 8:311-323 |
| ISSN: | 1361-8415 |
| DOI: | 10.1016/j.media.2004.06.009 |
| Popis: | Spatial normalization is a key process in cross-sectional studies of brain structure and function using MRI, fMRI, PET and other imaging techniques. A wide range of 2D surface and 3D image deformation algorithms have been developed, all of which involve design choices that are subject to debate. Moreover, most have numerical parameters whose value must be specified by the user. This paper proposes a principled method for evaluating design choices and choosing parameter values. This method can also be used to compare competing spatial normalization algorithms. We demonstrate the method through a performance analysis of a nonaffine registration algorithm for 3D images and a registration algorithm for 2D cortical surfaces. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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