ITK-SNAP: An interactive tool for semi-automatic segmentation of multi-modality biomedical images
University of Pennsylvania · University of Utah · +1 more institution
Abstract
Obtaining quantitative measures from biomedical images often requires segmentation, i.e., finding and outlining the structures of interest. Multi-modality imaging datasets, in which multiple imaging measures are available at each spatial location, are increasingly common, particularly in MRI. In applications where fully automatic segmentation algorithms are unavailable or fail to perform at desired levels of accuracy, semi-automatic segmentation can be a time-saving alternative to manual segmentation, allowing the human expert to guide segmentation, while minimizing the effort expended by the expert on repetitive tasks that can be automated. However, few existing 3D image analysis tools support semi-automatic…
Citation impact
- FWCI
- 6.93
- Percentile
- 100%
- References
- 14
Authors
3Topics & keywords
- Segmentation
- Modality (human–computer interaction)
- Computer science
- Artificial intelligence
- Image segmentation
- Scale-space segmentation
- Computer vision
- Context (archaeology)
- Life in Land