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Abstract
The segmentation of 2D images of 3D non-rigid objects into their constituent parts can pose challenging problems, such as missing and occluded parts, weak constraints over the spatial arrangement of parts, and variance in form and appearance. These problems have been addressed via segmentation methods that incorporate spatial context information, such as the auto-context technique. In this paper, we address for the first time the problem of segmenting multiple organs in images of pig offal, a challenging image analysis task that constitutes an essential step towards automated screening at abattoir for signs of sub-clinical diseases. We applied auto-context segmentation to a large data set of images and explored the effect of complementing conventional context features with integral features suited to our application.
Original language | English |
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Title of host publication | 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) |
Subtitle of host publication | From Nano to Macro, ISBI 2016 - Proceedings |
Publisher | IEEE |
Pages | 1324-1328 |
Number of pages | 5 |
Volume | June-2016 |
ISBN (Electronic) | 9781479923496 |
ISBN (Print) | 9781479923502 |
DOIs | |
Publication status | Published - 16 Jun 2016 |
Event | 2016 IEEE 13th International Symposium on Biomedical Imaging - Clarion Congress Hotel, Prague, Czech Republic Duration: 13 Apr 2016 → 16 Apr 2016 http://biomedicalimaging.org/2016/ (Link to Conference website) |
Conference
Conference | 2016 IEEE 13th International Symposium on Biomedical Imaging |
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Abbreviated title | ISBI 2016 |
Country/Territory | Czech Republic |
City | Prague |
Period | 13/04/16 → 16/04/16 |
Internet address |
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Keywords
- Context
- Feature extraction
- Training
- Image segmentation
- Heart
- Lungs
- Image color analysis
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