Multi-channel convolutional analysis operator learning for dual-energy CT reconstruction

Author:

Perelli AlessandroORCID,Alfonso Garcia Suxer,Bousse AlexandreORCID,Tasu Jean-Pierre,Efthimiadis Nikolaos,Visvikis Dimitris

Abstract

Abstract Objective. Dual-energy computed tomography (DECT) has the potential to improve contrast and reduce artifacts and the ability to perform material decomposition in advanced imaging applications. The increased number of measurements results in a higher radiation dose, and it is therefore essential to reduce either the number of projections for each energy or the source x-ray intensity, but this makes tomographic reconstruction more ill-posed. Approach. We developed the multi-channel convolutional analysis operator learning (MCAOL) method to exploit common spatial features within attenuation images at different energies and we propose an optimization method which jointly reconstructs the attenuation images at low and high energies with mixed norm regularization on the sparse features obtained by pre-trained convolutional filters through the convolutional analysis operator learning (CAOL) algorithm. Main results. Extensive experiments with simulated and real computed tomography data were performed to validate the effectiveness of the proposed methods, and we report increased reconstruction accuracy compared with CAOL and iterative methods with single and joint total variation regularization. Significance. Qualitative and quantitative results on sparse views and low-dose DECT demonstrate that the proposed MCAOL method outperforms both CAOL applied on each energy independently and several existing state-of-the-art model-based iterative reconstruction techniques, thus paving the way for dose reduction.

Funder

Agence Nationale de la Recherche

Publisher

IOP Publishing

Subject

Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Uconnect: Synergistic Spectral CT Reconstruction With U-Nets Connecting the Energy Bins;IEEE Transactions on Radiation and Plasma Medical Sciences;2024-02

2. Systematic Review on Learning-Based Spectral CT;IEEE Transactions on Radiation and Plasma Medical Sciences;2024-02

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