Markov-chain Monte Carlo-based image reconstruction for streak artefact reduction on contrast-enhanced computed tomography

摘要

Intervertebral disc herniation is a very common disorder and contrast-enhanced computed tomography (CECT) is one of the imaging modalities for studying the causes of intervertebral disc herniation and its potential link as a mechanical source of pain. However, streak artefacts caused by the contrast agent reduce the quality of the reconstructed image. We therefore propose a novel image reconstruction technique for reducing streak artefacts in CECT images of the intervertebral disc. The technique identifies the contrast agent-affected region in projection space using a multi-scale segmentation algorithm, which is followed by reconstruction via Markov-chain Monte Carlo estimation. The results were compared with two existing artefact-reducing techniques (non-iterative and iterative), and the proposed method showed an improvement on signal-to-noise ratio (53.1 dB) while non-iterative and iterative approaches yielded 26.5 and 48.4 dB, respectively. The proposed image reconstruction technique can reduce streak artefacts on CECT images of intervertebral disc herniation and it can be extended to other streak artefacts caused by the contrast agent on computed tomography images.