Meeting Banner
Abstract #0750

NUCLIDE: A Novel Unsupervised Clustering-based Image Denoising and Enhancement for 4D Dynamic PET/MRI Data

Hamed Yousefi1, Mahdjoub Hamdi2, Richard Laforest2, Matthew Brier2, Tammie Benzinger2, Yasheng Chen2, and Hongyu An2
1Washington University in St.Louis, Creve Coeur, MO, United States, 2Washington University in St. Louis, St. Louis, MO, United States

Synopsis

Keywords: AI/ML Image Reconstruction, AI/ML Image Reconstruction, 4D Dynamic PET/MRI

Motivation: Dynamic PET denoising through deep learning struggles with contrast preservation and activity fidelity, compounded by black-box models and the absence of paired noisy-clean PET data. Current methods often oversmooth, obscuring crucial details.

Goal(s): We propose an unsupervised 4D PET denoising approach that enhances image quality while maintaining TACs, leveraging the clustering of spatiotemporal features.

Approach: Our method utilizes K-means clustering on temporal PCA, spatial MRI, and anatomical features to create localized STC maps. Lowpass filtering is applied in a Radon-transformed feature space for targeted denoising without blurring.

Results: Results show improved SNR & CNR, with an error reduction of 54.2% on simulated OSEM data.

Impact: Our method enables robust, unsupervised denoising for PET/MRI, preserving critical TACs and structural information. This method has applications in clinical settings and is adaptable to multimodal imaging.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords