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Label Propagation
Posted on Monday, July 04 @ 05:07:32 BST by admin
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We are approaching a framework whereby labels (segmentation) can be bound to a single image and then automatically be used to infer the labelling in other images. This has the potential of saving a great deal of manual work which traditionally goes into segmenting images. Furthermore, since data from a group of images is used, there ought to be added robustness to noise. This helps in surpassring stand-alone segmentation, which is typically handled by investigating a single image at a time.
The framework, which relies on non-rigid registration, is illustrated schematically below.
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| Monday, July 25 | | · | Placing Labels at Strong Edges |
| Tuesday, July 19 | | · | Model Construction and Registration in Medical Imaging |
| Thursday, July 14 | | · | Euclidean Image Distance |
| Thursday, July 07 | | · | Evaluation of Appearance Models |
| Tuesday, July 05 | | · | Parallel Work |
| Monday, July 04 | | · | Label Propagation |
| Sunday, July 03 | | · | Segmentation Propagation from Model |
| Friday, July 01 | | · | Segmentation in Relation to Models and NRR |
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| Thursday, June 30 | | · | 3-D Surface Visualisation |
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| Wednesday, June 29 | | · | Simultaneous Segmentation, Registration and Models |
| · | Migration from AART to MARS |
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