Article: article from journal or magazin.
Atlas-based segmentation of pathological MR brain images using a model of lesion growth.
Ieee Transactions On Medical Imaging
Publication types: Comparative Study ; Evaluation Studies ; Journal Article ; Research Support, Non-U.S. Gov't ; Validation StudiesPublication Status: ppublish
We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.
Algorithms, Anatomy, Artistic/methods, Artificial Intelligence, Brain Neoplasms/diagnosis, Cluster Analysis, Computer Simulation, Humans, Image Enhancement/methods, Image Interpretation, Computer-Assisted/methods, Imaging, Three-Dimensional/methods, Information Storage and Retrieval/methods, Magnetic Resonance Imaging/methods, Medical Illustration, Meningeal Neoplasms/diagnosis, Meningioma/diagnosis, Models, Biological, Models, Statistical, Pattern Recognition, Automated/methods, Reproducibility of Results, Sensitivity and Specificity, Subtraction Technique
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