Abstract
This paper presents a novel, unsupervised method for segmenting tumours in PET data. The method uses region-based active surface modelling in a hierarchical scheme to eliminate segmentation errors, followed by an alpha matting step to further refine the segmentation. We have validated our method on real PET images of head-and-neck cancer patients as well as custom designed phantom PET images. Experiments show that our method can generate more accurate segmentation than some previous approaches.
| Original language | English |
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| Pages | 131-136 |
| Number of pages | 6 |
| Publication status | Published - 09 Jul 2012 |
| Event | 16th Conference on Medical Image Understanding and Analysis 2012 - Swansea, United Kingdom of Great Britain and Northern Ireland Duration: 09 Jul 2012 → 11 Jul 2012 |
Conference
| Conference | 16th Conference on Medical Image Understanding and Analysis 2012 |
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| Abbreviated title | MIUA 2012 |
| Country/Territory | United Kingdom of Great Britain and Northern Ireland |
| City | Swansea |
| Period | 09 Jul 2012 → 11 Jul 2012 |
