ArticleJournal of biomedical optics2017
Anatomical image-guided fluorescence molecular tomography reconstruction using kernel method.
Article in Journal of biomedical optics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed, 27 citations in OpenAlex.
- Liver injury monitoring using dynamic fluorescence molecular tomography based on a time-energy difference strategy.Biomedical optics express · 2023Article
- Multi-target reconstruction strategy based on blind source separation of surface measurement signals in FMT.Biomedical optics express · 2023Article
- Excitation-based fully connected network for precise NIR-II fluorescence molecular tomography.Biomedical optics express · 2022Article
- Intercomparison of MR-informed PET image reconstruction methods.Medical physics · 2019Article
- High Temporal-Resolution Dynamic PET Image Reconstruction Using a New Spatiotemporal Kernel Method.IEEE transactions on medical imaging · 2019Article
- Regularized reconstruction based on joint LBiomedical optics express · 2019Article
- Recent methodology advances in fluorescence molecular tomography.Visual computing for industry, biomedicine, and art · 2018Review
- Spatially-Compact MR-Guided Kernel EM for PET Image Reconstruction.IEEE transactions on radiation and plasma medical sciences · 2018Article
- MR-Guided Kernel EM Reconstruction for Reduced Dose PET Imaging.IEEE transactions on radiation and plasma medical sciences · 2018Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Fluorescence molecular tomography (FMT) is an important in vivo imaging modality to visualize physiological and pathological processes in small animals. However, FMT reconstruction is ill-posed and ill-conditioned due to strong optical scattering in deep tissues, which results in poor spatial resolution. It is well known that FMT image quality can be improved substantially by applying the structural guidance in the FMT reconstruction. An approach to introducing anatomical information into the FMT reconstruction is presented using the kernel method. In contrast to conventional methods that incorporate anatomical information with a Laplacian-type regularization matrix, the proposed method introduces the anatomical guidance into the projection model of FMT. The primary advantage of the proposed method is that it does not require segmentation of targets in the anatomical images. Numerical simulations and phantom experiments have been performed to demonstrate the proposed approach’s feasibility. Numerical simulation results indicate that the proposed kernel method can separate two FMT targets with an edge-to-edge distance of 1 mm and is robust to false-positive guidance and inhomogeneity in the anatomical image. For the phantom experiments with two FMT targets, the kernel method has reconstructed both targets successfully, which further validates the proposed kernel method.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.