Polychromatic neural CBCT reconstruction through density-attenuation modeling.
Authors
Affiliations (3)
Affiliations (3)
- Johannes Gutenberg University Mainz, Staudingerweg 9, Mainz, 55128, GERMANY.
- University Of Applied Sciences Wiesbaden, Unter den Eichen 5, Wiesbaden, HE, 65195, GERMANY.
- Division of Oral Diagnostic Sciences, Clinic of Oral Surgery and Stomatology, University of Bern, Freiburgstrasse 7, Bern, Bern, 3010, SWITZERLAND.
Abstract
Monochromatic CBCT reconstruction algorithms are still most prominent in practice. Since the X-ray detectors of today's machines are mostly energy integrating detectors and thus not able to resolve photon energy levels, reconstruction artefacts, often termed as beam-hardening artefacts, are a frequent observation. We propose a polychromatic 3D reconstruction technique, using a coordinate based neural representation, that requires zero additional prior information, in which we model attenuation related to a fixed energy level E<sub>0</sub>together with its derivative. We concurrently optimize an intermediate density value for each spatial position together with a composite attenuation function. It assigns each intermediate density value its attenuation coefficient and computes the derivative of the attenuation coefficient w.r.t. the energy. We implement this function as a neural network that models a monotonic relationship between intermediate density and attenuation. In our results we can show that the proposed method is able to considerably improve reconstruction quality in various scenarios, both quantitatively using a synthetic numerical phantom as well as visual quality in real-world clinical examples.