Name
Title | ||
|---|---|---|
Automatic detection of structural changes in single channel long time-span brain MRI images using saliency map and active contour methods |
Abstract | ||
|---|---|---|
This paper introduces a novel method to detect structural changes between MRI scans, without using prior knowledge. After a simple registration step, the method calculates a difference image, based on modified Harris saliency function, which is then used to define change candidates. Localization step filters out false hits with local contour descriptors featuring the neighborhood of candidates. Finally, boundary of the lesion is detected by integration of contour point extraction and Chan-Vese active contour method. Tests on simulated and real data show that the results are very promising. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICIP.2012.6467097 | Image Processing |
Keywords | Field | DocType |
biomedical MRI,brain,edge detection,feature extraction,filtering theory,image registration,medical image processing,object detection,Chan-Vese active contour method,Harris saliency function,automatic structural changes detection,contour point extraction,difference image calculation,lesion boundary detection,local contour descriptors,localization step,registration step,saliency map,single channel long time-span brain MRI images,Harris saliency function,biomedical imaging,change detection,local contour descriptors,magnetic resonance imaging (MRI) | Active contour model,Object detection,Computer vision,Change detection,Pattern recognition,Salience (neuroscience),Medical imaging,Edge detection,Computer science,Feature extraction,Artificial intelligence,Image registration | Conference |
ISSN | ISBN | Citations |
1522-4880 E-ISBN : 978-1-4673-2532-5 | 978-1-4673-2532-5 | 0 |
PageRank | References | Authors |
0.34 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrea Kovács | 1 | 37 | 3.56 |
| Tamás Szirányi | 2 | 152 | 26.92 |
| Peter Barsi | 3 | 0 | 0.34 |