eprintid: 10128563 rev_number: 14 eprint_status: archive userid: 608 dir: disk0/10/12/85/63 datestamp: 2021-05-27 16:32:00 lastmod: 2021-09-25 22:51:15 status_changed: 2021-05-27 16:32:00 type: article metadata_visibility: show creators_name: Tsai, Y-J creators_name: Bousse, A creators_name: Arridge, S creators_name: Stearns, CW creators_name: Hutton, BF creators_name: Thielemans, K title: Penalized PET/CT Reconstruction Algorithms With Automatic Realignment for Anatomical Priors ispublished: pub divisions: UCL divisions: B02 divisions: C10 divisions: D17 divisions: FI6 divisions: B04 divisions: C05 divisions: F48 keywords: Anatomical prior, misalignment estimation, penalized image reconstruction note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. abstract: Two algorithms for solving misalignment issues in penalized PET/CT reconstruction using anatomical priors are proposed. Both approaches are based on a recently published joint motion estimation and image reconstruction method. The first approach deforms the anatomical image to align it with the functional one while the second approach deforms both images to align them with the measured data. Our current implementation alternates between alignment estimation and image reconstruction. We have chosen parallel level sets (PLSs) as a representative anatomical penalty, incorporating a spatially variant penalty strength. The performance was evaluated using simulated nontime-of-flight data generated with an XCAT phantom in the thorax region. We used the attenuation map in the anatomical prior. The results demonstrated that both methods can estimate the misalignment and deform the anatomical image accordingly. However, the performance of the first approach depends highly on the workflow of the alternating process. The second approach shows a faster convergence rate to the correct alignment and is less sensitive to the workflow. The presence of anatomical information improves the convergence rate of misalignment estimation for the second approach but slow it down for the first approach. Both approaches show improved performance in misalignment estimation as the data noise level decreases. date: 2021-05 date_type: published publisher: Institute of Electrical and Electronics Engineers (IEEE) official_url: https://doi.org/10.1109/TRPMS.2020.3025540 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 1862373 doi: 10.1109/trpms.2020.3025540 lyricists_name: Arridge, Simon lyricists_name: Hutton, Brian lyricists_name: Thielemans, Kris lyricists_id: SRARR14 lyricists_id: BHUTT63 lyricists_id: KTHIE60 actors_name: Thielemans, Kris actors_id: KTHIE60 actors_role: owner full_text_status: public publication: IEEE Transactions on Radiation and Plasma Medical Sciences volume: 5 number: 3 pagerange: 362-372 citation: Tsai, Y-J; Bousse, A; Arridge, S; Stearns, CW; Hutton, BF; Thielemans, K; (2021) Penalized PET/CT Reconstruction Algorithms With Automatic Realignment for Anatomical Priors. IEEE Transactions on Radiation and Plasma Medical Sciences , 5 (3) pp. 362-372. 10.1109/trpms.2020.3025540 <https://doi.org/10.1109/trpms.2020.3025540>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10128563/1/journal_submission_on_joint_reconstruction.pdf