Multi-atlas automatic positioning of anatomical landmarks
| Autor: | Sébastien Valette, Hector Jacinto, Rémy Prost |
|---|---|
| Přispěvatelé: | Images et Modèles, Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM) |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Landmark
Computer science Atlas (topology) business.industry Multi atlas Anatomical structures ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Iterative closest point 020207 software engineering 02 engineering and technology [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] Signal Processing 0202 electrical engineering electronic engineering information engineering Media Technology 020201 artificial intelligence & image processing Computer vision Polygon mesh Computer Vision and Pattern Recognition Artificial intelligence Electrical and Electronic Engineering business ComputingMilieux_MISCELLANEOUS |
| Zdroj: | Journal of Visual Communication and Image Representation Journal of Visual Communication and Image Representation, Elsevier, 2018, 50, pp.167-177 |
| ISSN: | 1047-3203 1095-9076 |
| Popis: | We propose a method for the automatic positioning of pre-defined landmarks on 3-D models of anatomical structures. We exploit a group of atlases consisting of multiple triangular meshes for which the defined landmarks have been placed by experts. We compute an initial coarse global registration of the patient mesh with an expert mesh by using a curvature-enhanced Iterative Closest Point (ICP) algorithm. Adaptive local rigid registrations refine the fit for the projection of reference landmarks onto the surface of the patient structure. An automatic selection based on a fit criterion computes a final position for each landmark. Our positioning method improves the efficiency of the positioning task, being completely unsupervised and yielding results competitive with those of the manual positioning. We provide comparisons with previous works of the literature. The automatic positioning for each target structure is completely reproducible as opposed to manual positioning, affected by intra-operator variability. |
| Databáze: | OpenAIRE |
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