Noise-Robust One-Bit Diffraction Tomography and Optimal Dose Fractionation
Fuente:
arXiv
Guardado en:
| Autores principales: | , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2023
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866908376799117312 |
|---|---|
| author | Chen, Pengwen Fannjiang, Albert |
| author_facet | Chen, Pengwen Fannjiang, Albert |
| contents | This study presents a noise-robust framework for 1-bit diffraction tomography, a novel imaging approach that relies on intensity-only binary measurements obtained through coded apertures. The proposed reconstruction scheme leverages random matrix theory and iterative algorithms to effectively recover 3D object structures under high-noise conditions.
A key contribution is the numerical investigation of dose fractionation, revealing optimal performance at a signal-to-noise ratio near 1, {\em independent of the total dose}. This finding addresses the question: How to distribute a given level of total radiation energy among different tomographic views in order to optimize the quality of reconstruction? |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_05571 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Noise-Robust One-Bit Diffraction Tomography and Optimal Dose Fractionation Chen, Pengwen Fannjiang, Albert Information Theory Data Analysis, Statistics and Probability This study presents a noise-robust framework for 1-bit diffraction tomography, a novel imaging approach that relies on intensity-only binary measurements obtained through coded apertures. The proposed reconstruction scheme leverages random matrix theory and iterative algorithms to effectively recover 3D object structures under high-noise conditions. A key contribution is the numerical investigation of dose fractionation, revealing optimal performance at a signal-to-noise ratio near 1, {\em independent of the total dose}. This finding addresses the question: How to distribute a given level of total radiation energy among different tomographic views in order to optimize the quality of reconstruction? |
| title | Noise-Robust One-Bit Diffraction Tomography and Optimal Dose Fractionation |
| topic | Information Theory Data Analysis, Statistics and Probability |
| url | https://arxiv.org/abs/2310.05571 |