AIRPORT : A Data Consistency Constrained Deep Temporal Extrapolation Method To Improve Temporal Resolution In Contrast Enhanced CT Imaging

Typical tomographic image reconstruction methods require that the imaged object is static and stationary during the time window to acquire a minimally complete data set. The violation of this requirement leads to temporal-averaging errors in the reconstructed images. For a fixed gantry rotation speed, to reduce the errors, it is desired to reconstruct images using data acquired over a narrower angular range, i.e., with a higher temporal resolution. However, image reconstruction with a narrower angular range violates the data sufficiency condition, resulting in severe data-insufficiency-induced errors. The purpose of this work is to decouple the trade-off between these two types of errors in contrast-enhanced computed tomography (CT) imaging. We demonstrated that using the developed data consistency constrained deep temporal extrapolation method (AIRPORT), the entire time-varying imaged object can be accurately reconstructed with 40 frames-per-second temporal resolution, the time window needed to acquire a single projection view data using a typical C-arm cone-beam CT system. AIRPORT is applicable to general non-sparse imaging tasks using a single short-scan data acquisition.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:43

Enthalten in:

IEEE transactions on medical imaging - 43(2024), 4 vom: 22. Apr., Seite 1605-1618

Sprache:

Englisch

Beteiligte Personen:

Li, Yinsheng [VerfasserIn]
Feng, Juan [VerfasserIn]
Xiang, Jun [VerfasserIn]
Li, Zixiao [VerfasserIn]
Liang, Dong [VerfasserIn]

Links:

Volltext

Themen:

Journal Article

Anmerkungen:

Date Completed 04.04.2024

Date Revised 04.04.2024

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1109/TMI.2023.3344712

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM366246240