Local-mean preserving post-processing step for non-negativity enforcement in PET imaging: application to $^{90}$Y-PET

Autor: Millardet, Maël, Moussaoui, Saïd, Mateus, Diana, Idier, Jérôme, Carlier, Thomas

In a low-statistics PET imaging context, the positive bias in regions of low activity is a burning issue. To overcome this problem, algorithms without the built-in non-negativity constraint may be used. They allow negative voxels in the image to redu

Externí odkaz: http://arxiv.org/abs/2012.06432

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Amélioration de la quantification des images TEP à l'yttrium 90

Autor: Millardet, Maël

Publikováno v: Imagerie médicale. École Centrale de Nantes, 2022. Français. ⟨NNT : ⟩
Algorithme et structure de données [cs.DS]. École centrale de Nantes, 2022. Français. ⟨NNT : 2022ECDN0016⟩

Yttrium-90 PET imaging is becoming increasingly popular. However, the probability that decay of a yttrium-90 nucleus will lead to the emission of a positron is only 3.2 × 10−5, and the reconstructed images are therefore characterised by a high lev

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::cfc293a633b7c703844054c7aa22f496
https://hal.science/tel-03697381/file/these_version_finale.pdf

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Low-count PET image reconstruction with Bayesian inference over a Deep Prior

Autor: Išgum, Ivana, Landman, Bennett A., Carrillo, Hernan, Millardet, Maël, Carlier, Thomas, Mateus, Diana

Publikováno v: Proceedings of SPIE; February 2021, Vol. 11596 Issue: 1 p115960V-115960V-9, 1043650p