A Bayesian nonparametric approach to tumor detection using UWB imaging
We develop a tumor detection and discrimination algorithm for Ultra-Wideband (UWB) microwave imaging of breast cancer based on a Bayesian nonparametric approach. We model the UWB backscattered signal as a mixture of distinct scatterer contributions, and use a Dirichlet Process mixture model (DPMM) t...
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| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2013
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| Online Access: | https://hdl.handle.net/10356/99490 http://hdl.handle.net/10220/12892 |
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| Institution: | Nanyang Technological University |
| Language: | English |