Improved Watershed Transform for Medical Image Segmentation Using Prior Information
Universitat Politècnica de València · Harvard University · +1 more institution
Abstract
The watershed transform has interesting properties that make it useful for many different image segmentation applications: it is simple and intuitive, can be parallelized, and always produces a complete division of the image. However, when applied to medical image analysis, it has important drawbacks (oversegmentation, sensitivity to noise, poor detection of thin or low signal to noise ratio structures). We present an improvement to the watershed transform that enables the introduction of prior information in its calculation. We propose to introduce this information via the use of a previous probability calculation. Furthermore, we introduce a method to combine the watershed transform and atlas registration,…
Citation impact
- FWCI
- 26.51
- Percentile
- 100%
- References
- 52
Authors
5- VGVicente GrauCorresponding
Universitat Politècnica de València, Harvard University, Brigham and Women's Hospital
- AUAndrea U. J. Mewes
Harvard University, Brigham and Women's Hospital
- MAMariano Alcañíz
Universitat Politècnica de València
- RKRon Kikinis
Brigham and Women's Hospital, Harvard University
- SKSimon K. Warfield
Brigham and Women's Hospital, Harvard University
Topics & keywords
- Watershed
- Artificial intelligence
- Computer science
- Image segmentation
- Segmentation
- Computer vision
- Image registration
- Scale-space segmentation
- Life in Land