Model-based segmentation of medical imagery by matching distributions Journal Article
| Authors: | Freedman, D.; Radke, R. J.; Zhang, T.; Jeong, Y.; Lovelock, D. M.; Chen, G. T. Y. |
| Article Title: | Model-based segmentation of medical imagery by matching distributions |
| Abstract: | The segmentation of deformable objects from three-dimensional (3-D) images is an important and challenging problem, especially in the context of medical imagery. We present a new segmentation algorithm based on matching probability distributions of photometric variables that incorporates learned shape and appearance models for the objects of interest. The main innovation over similar approaches is that there is no need to compute a pixelwise correspondence between the model and the image. This allows for a fast, principled algorithm. We present promising results on difficult imagery for 3-D computed tomography images of the male pelvis for the purpose of image-guided radiotherapy of the prostate. © 2005 IEEE. |
| Keywords: | three dimensional; magnetic resonance imaging; image analysis; radiotherapy; algorithms; prostate cancer; computerized tomography; medical imaging; computer vision; deformable segmentation; shape and appearance model; image segmentation; medical image segmentation; image-guided therapy; prostate segmentation; object recognition |
| Journal Title: | IEEE Transactions on Medical Imaging |
| Volume: | 24 |
| Issue: | 2 |
| ISSN: | 0278-0062 |
| Publisher: | IEEE |
| Date Published: | 2005-03-01 |
| Start Page: | 281 |
| End Page: | 292 |
| Language: | English |
| DOI: | 10.1109/tmi.2004.841228 |
| PROVIDER: | scopus |
| PUBMED: | 15754979 |
| DOI/URL: | |
| Notes: | --- - "Cited By (since 1996): 64" - "Export Date: 24 October 2012" - "CODEN: ITMID" - "Source: Scopus" |
