Compensating for Limited Spatial Resolution of Positron Emission Tomography, Upcoming Webinar Hosted by Xtalks


Details on the practical implementation of a PVC scheme on large patient cohorts and in a mostly unsupervised fashion will be presented through the description of image processing pipelines.

While positron emission tomography (PET) has the unique ability to probe living cells in a non-invasive and highly sensitive manner, it is still plagued with relatively low spatial resolution compared to anatomy-oriented imaging devices such as MRI or CT.

This webinar will present an overview of the techniques used to compensate for the limited spatial resolution of emission tomography imaging systems such as PET, as applied to the human brain. Starting with the fundamental principles of PET and the factors affecting spatial resolution, the speaker will then dive into a detailed description of the fundamental aspects of the object-image relationship and the general problem of image restoration.

A review of the various methods developed over the past 30 years to compensate for the so-called partial volume (PV) effects will follow. Emphasis will be given to the most widely used methods in current use today, concentrating on post-reconstruction PV correction (PVC) methods, and discussing their fundamental differences.

Details on the practical implementation of a PVC scheme on large patient cohorts and in a mostly unsupervised fashion will be presented through the description of image processing pipelines. Characterization of the interaction between the radioactivity distribution and the PET scanner will be discussed in terms of brain segmentation, and the scanner’s effective spatial resolution assessment through physical phantom experiments.

Join Olivier Rousset, PhD, PET Scientist, Neuroscience, Bioclinica in a live webinar on Thursday, October 7, 2021 at 11:30am EDT (4:30pm BST/UK).

For more information, or to register for this event, visit Compensating for Limited Spatial Resolution of Positron Emission Tomography.

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