A two-stage reconstruction of fluorescence molecular tomography based on sparse regularization
Fluorescence molecular tomography (FMT) is a promising imaging modality that offers the possibilities to monitor cellular and molecular function in vivo. However, accurate and stable reconstruction of fluorescence-labeled targets remains a challenging problem. In this contribution, a two-stage recon...
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| Veröffentlicht in: | 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2013, Vol.2013, p.3415-3418 |
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| container_title | 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |
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| creator | Cheng, Jingxing Hou, Yuqing Yu, Jingjing He, Xiaowei |
| description | Fluorescence molecular tomography (FMT) is a promising imaging modality that offers the possibilities to monitor cellular and molecular function in vivo. However, accurate and stable reconstruction of fluorescence-labeled targets remains a challenging problem. In this contribution, a two-stage reconstruction algorithm that combines sparse regularization with adaptive finite element method is proposed, and two different inversion algorithms are employed separately on the initial coarse mesh and the second refined one. Numerical experiment results with a digital mouse model demonstrate the stability and computational efficiency of the proposed method for FMT. |
| doi_str_mv | 10.1109/EMBC.2013.6610275 |
| format | Article |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Algorithms Animals Finite element analysis Fluorescence Image Processing, Computer-Assisted - methods Image reconstruction Mathematical model Mice Organ Specificity Phantoms, Imaging Reconstruction algorithms Tomography - methods |
| title | A two-stage reconstruction of fluorescence molecular tomography based on sparse regularization |
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