Volumetric texture segmentation by discriminant feature selection and multiresolution classification
Reyes Aldasoro, Constantino Carlos and Bhalerao, Abhir. (2007) Volumetric texture segmentation by discriminant feature selection and multiresolution classification. IEEE Transactions on Medical Imaging, Volume 26 (Number 1). pp. 1-14. ISSN 0278-0062Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/TMI.2006.884637
In this paper, a multiresolution volumetric texture segmentation (M-VTS) algorithm is presented. The method extracts textural measurements from the Fourier domain of the data via subband filtering using an orientation pyramid (Wilson and Spann, 1988). A novel Bhattacharyya space, based on the Bhattacharyya distance, is proposed for selecting the most discriminant measurements and producing a compact feature space. An oct tree is built of the multivariate features space and a chosen level at a lower spatial resolution is first classified. The classified voxel labels are then projected to lower levels of the tree where a boundary refinement procedure is performed with a three-dimensional (3-D) equivalent of butterfly filters. The algorithm was tested with 3-D artificial data and three magnetic resonance imaging sets of human knees with encouraging results. The regions segmented from the knees correspond to anatomical structures that can be used as a starting point for other measurements such as cartilage extraction.
|Item Type:||Journal Article|
|Subjects:||Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TR Photography
|Divisions:||Faculty of Science > Computer Science|
|Journal or Publication Title:||IEEE Transactions on Medical Imaging|
|Official Date:||January 2007|
|Number of Pages:||14|
|Page Range:||pp. 1-14|
|Access rights to Published version:||Restricted or Subscription Access|
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