Report
A Convex Reconstruction Model for X-ray Tomographic Imaging with Uncertain Flat-fields
| العنوان: | A Convex Reconstruction Model for X-ray Tomographic Imaging with Uncertain Flat-fields |
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| المؤلفون: | Aggrawal, Hari Om, Andersen, Martin Skovgaard, Rose, Sean, Sidky, Emil Y. |
| سنة النشر: | 2017 |
| المجموعة: | Mathematics Statistics |
| مصطلحات موضوعية: | Mathematics - Numerical Analysis, Statistics - Applications |
| الوصف: | Classical methods for X-ray computed tomography are based on the assumption that the X-ray source intensity is known, but in practice, the intensity is measured and hence uncertain. Under normal operating conditions, when the exposure time is sufficiently high, this kind of uncertainty typically has a negligible effect on the reconstruction quality. However, in time- or dose-limited applications such as dynamic CT, this uncertainty may cause severe and systematic artifacts known as ring artifacts. By carefully modeling the measurement process and by taking uncertainties into account, we derive a new convex model that leads to improved reconstructions despite poor quality measurements. We demonstrate the effectiveness of the methodology based on simulated and real data sets. Comment: Accepted at IEEE Transactions on Computational Imaging |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1109/TCI.2017.2723246 |
| URL الوصول: | http://arxiv.org/abs/1707.04531 |
| رقم الانضمام: | edsarx.1707.04531 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1109/TCI.2017.2723246 |
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