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Inpainting-filtering for metal artifact reduction (IMIF-MAR) in computed tomography

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Abstract

The reduction of metal artifacts remains a challenge in computed tomography because they decrease image quality, and consequently might affect the medical diagnosis. The objective of this study is to present a novel method to correct metal artifacts based solely on the CT-slices. The proposed method consists of four steps. First, metal implants in the original CT-slice are segmented using an entropy based method, producing a metal image. Second, a prior image is acquired using three transformations: Gaussian filter, Parisotto and Schoenlieb inpainting method with the Mumford-Shah image model and L0 Gradient Minimization method (L0GM). Next, based on the projections from the original CT-slice, prior image and metal image, the sinogram is corrected in the traces affected by metal in the process called normalization and denormalization. Finally, the reconstructed image is obtained by FBP and a Nonlocal Means (NLM) filtering. The efficacy of the algorithm is evaluated by comparing five image quality metrics of the images and by inspecting regions of interest (ROI). Phantom data as well as clinical datasets are included. The proposed method is compared with three established metal artifact reduction (MAR) methods. The results from a phantom and clinical dataset show the visible reduction of artifacts. The conclusion is that IMIF-MAR method can reduce streak metal artifacts effectively and avoid new artifacts around metal implants, while preserving the anatomical structures. Considering both clinical and phantom studies, the proposed MAR algorithm improves the quality of clinical images affected by metal artifacts, and could be integrated in clinical setting.

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Acknowledgements

The authors gratefully acknowledge funding by the Deutscher Akademischer Austauschdienst (DAAD) as well as funding by the Federal Ministry of Education and Research within the Forschungscampus STIMULATE under grant number '13GW0095A'. We thank Professor Georg Rose for his support and guidance. Also, thanks to Vojtech Kulvait, Robert Frysch, Cindy Lübeck for their assistance in imaging experiments, and Dr. Oliver Beuing from the University Hospital Magdeburg for his collaboration.

Funding

This paper was done by funding the Deutscher Akademischer Austauschdienst (DAAD) as well as funding by the Federal Ministry of Education and Research within the Forschungscampus STIMULATE under Grant Number '13GW0095A'.

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Authors and Affiliations

  1. Departamento de Electrónica y Telecomunicaciones, Universidad Central ‘Marta Abreu’ de Las Villas, Santa Clara, Cuba

    Yakdiel Rodríguez-Gallo

  2. Departamento de Control Automático, Universidad Central ‘Marta Abreu’ de Las Villas, Carretera a Camajuani km 5 ½, 54830, Santa Clara, Villa Clara, Cuba

    Rubén Orozco-Morales & Marlen Pérez-Díaz

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  1. Yakdiel Rodríguez-Gallo
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  3. Marlen Pérez-Díaz
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Correspondence to Marlen Pérez-Díaz.

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The authors declare that they have no conflict of interest.

Ethical approval

The code was programmed in Matlab R 2018 b and it will be sent to the Journal if necessary All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Part of the data was previously used in Magdeburg University and it was donated for our work. The patient data acquired by us and used in a previous article, was approved by the Ethics Committee: "Cardiocentro de Villa Clara". Approval number 12/2017.

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Informed consent was previously obtained from individual participants included in the study. Images 6, 7, 8, 9 and 10 were properly anonymized for publication purposes. There are not details in the work that reveal the identity of the patients. Patient consent for publication, is not applicable.

All authors have actively contributed to this article through data collection, development of experiments, analysis of results and writing the article.

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Rodríguez-Gallo, Y., Orozco-Morales, R. & Pérez-Díaz, M. Inpainting-filtering for metal artifact reduction (IMIF-MAR) in computed tomography. Phys Eng Sci Med 44, 409–423 (2021). https://doi.org/10.1007/s13246-021-00990-8

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  • DOI: https://doi.org/10.1007/s13246-021-00990-8

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