Name
Abstract | ||
|---|---|---|
In this paper, we propose a methodology to automatically carry out registration of hands out of conventional X-ray images. The registration method we describe here will be referred to as ''articulated registration''; the method is a landmark-based elastic registration procedure in which individual bones are affinely registered and soft tissues are elastically registered so that long skeletal structures are maintained straight while a continuous and smooth transformation is obtained all over the image. In order for the method to be fully automatic, the landmarks used for the registration are detected using a number of image processing algorithms. An optimization step for the refinement of the landmarks locations is included within the registration algorithm; the algorithm is based on an iterative procedure to maximize a local similarity measure. A final procedure to correct bone width has also been performed. We show that the articulated registration described here is robust and outperforms alternatives based on the thin-plate splines (TPS) algorithm. The algorithm for automatic landmark position finding has been tested using registered images with landmarks manually selected by an expert. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.imavis.2008.11.001 | Image Vision Comput. |
Keywords | Field | DocType |
anatomical structures,automatic landmark position finding,elastic registration,hand radiograph,landmarks location,iterative procedure,bone age assessment,deformable geometry,landmark-based elastic registration procedure,final procedure,landmarks detection,image processing algorithm,registered image,automatic articulated registration,segmentation,articulated registration,registration algorithm,registration method,image processing,bone age,thin plate spline,soft tissue | Spline (mathematics),Computer vision,Similarity measure,Pattern recognition,Segmentation,Registration procedure,Artificial intelligence,Radiography,Landmark,Digital image processing,Mathematics,Bone width | Journal |
Volume | Issue | ISSN |
27 | 8 | Image and Vision Computing |
Citations | PageRank | References |
10 | 0.86 | 26 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miguel Á. Martín-Fernández | 1 | 10 | 0.86 |
| Rubén Cárdenes | 2 | 116 | 13.02 |
| Emma Muñoz-Moreno | 3 | 74 | 7.93 |
| Rodrigo de Luis-García | 4 | 150 | 14.15 |
| Marcos Martín-Fernández | 5 | 209 | 25.16 |
| Carlos Alberola-López | 6 | 482 | 52.95 |