Information-based analysis of X-ray in-line phase tomography with application to the detection of iron oxide nanoparticles in the brain

Hugo Rositi, Carole Frindel, Max Langer, Marlène Wiart, Cécile Olivier, Françoise Peyrin, David Rousseau

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

The study analyzes noise in X-ray in-line phase tomography in a biomedical context. The impact of noise on detection of iron oxide nanoparticles in mouse brain is assessed. The part of the noise due to the imaging system and the part due to biology are quantitatively expressed in a Neyman Pearson detection strategy with two models of noise. This represents a practical extension of previous work on noise in phase-contrast X-ray imaging which focused on the theoretical expression of the signal-tonoise ratio in mono-dimensional phantoms, taking account of the statistical noise of the imaging system only. We also report the impact of the phase retrieval step on detection performance. Taken together, this constitutes a general methodology of practical interest for quantitative extraction of information from X-ray in-line phase tomography, and is also relevant to assessment of contrast agents with a blob-like signature in high resolution imaging.

Original languageEnglish
Pages (from-to)27185-27196
Number of pages12
JournalOptics Express
Volume21
Issue number22
DOIs
Publication statusPublished - 2013 Nov 4
Externally publishedYes

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

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