Three-dimensional nonlinear invisible boundary detection.
Where this comes from
- Record sourced from PubMed, PMID 17022267.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
The human vision system can discriminate regions which differ up to the second-order statistics only. We present an algorithm designed to reveal "hidden" boundaries in gray level images, by computing gradients in higher order statistics of the data. We demonstrate it by applying it to the identification of possible "hidden" boundaries of glioblastomas as manifest themselves in three-dimensional (3-D) MRI scans, using a model driven approach. We also demonstrate the method using a nonmodel driven approach where we have no prior information about the location of possible boundaries. In this case, we use 3-D MRI data concerning schizophrenic patients and normal controls.
Medical subject headings
- Artificial Intelligence
- Brain Neoplasms
- Glioblastoma
- Image Enhancement
- Image Interpretation, Computer-Assisted
- Imaging, Three-Dimensional
- Pattern Recognition, Automated