Accurate and robust quantification of hybrid MRI-PET and PET-CT images through a novel joint-segmentation method
Molecular Imaging of Infectious Diseases: Current Status and Future Challenges
Abstract
An abstract is not available in the lab archive. View the paper at its source.
A 2012 meeting contribution on joint segmentation of hybrid MRI-PET and PET-CT images. The Machine and Hybrid Intelligence Lab’s publications page lists it as receiving a Best Poster Prize.
Summary
The Machine and Hybrid Intelligence Lab’s publications page lists this work in *Molecular Imaging of Infectious Diseases: Current Status and Future Challenges* (2012) and identifies it as a Best Poster Prize recipient. The title describes a joint-segmentation method for quantifying hybrid MRI-PET and PET-CT images. The available source does not provide an abstract or details of the method’s evaluation, results, or limitations.
Cite this work
N. Mendhiratta, Z. Xu, B. Foster, U. Bagci, and D. Mollura (2012). Accurate and robust quantification of hybrid MRI-PET and PET-CT images through a novel joint-segmentation method. Molecular Imaging of Infectious Diseases: Current Status and Future Challenges
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