IDART : An Improved Discrete Tomography Algorithm for Reconstructing Images With Multiple Gray Levels
The discrete algebraic reconstruction technique has many advantages in computed tomography and electron tomography. However, the number of gray levels and the absolute gray values that should be known in advance are typically not available in experiments especially when there are many gray levels in...
| Publié dans: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 31(2022) vom: 22., Seite 2608-2619 |
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| Auteur principal: | |
| Autres auteurs: | , , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2022
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| Accès à la collection: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Sujets: | Journal Article |
| Résumé: | The discrete algebraic reconstruction technique has many advantages in computed tomography and electron tomography. However, the number of gray levels and the absolute gray values that should be known in advance are typically not available in experiments especially when there are many gray levels in the image. In this paper, we report an automatic discrete tomography reconstruction algorithm to improve its feasibility in practice, without needing to know these two parameters. In our algorithm, the number of gray levels is estimated by labeling the connected components in the tomogram and the absolute values of them are determined by the modal value of each domain. The proposed algorithm was extensively validated on both simulated and experimental datasets. The results show that our algorithm can accurately recover not only the morphology but also the gray levels of the interested objects, even in the images with multiple gray levels. It is demonstrated that the presented algorithm is robust for eliminating missing wedge artifacts and tolerable for noisy data |
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| Description: | Date Revised 22.03.2022 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 1941-0042 |
| DOI: | 10.1109/TIP.2022.3152632 |