Core Imaging Library - Part I: a versatile Python framework for tomographic imaging.
Philos Trans A Math Phys Eng Sci
; 379(2204): 20200192, 2021 Aug 23.
Article
en En
| MEDLINE
| ID: mdl-34218673
ABSTRACT
We present the Core Imaging Library (CIL), an open-source Python framework for tomographic imaging with particular emphasis on reconstruction of challenging datasets. Conventional filtered back-projection reconstruction tends to be insufficient for highly noisy, incomplete, non-standard or multi-channel data arising for example in dynamic, spectral and in situ tomography. CIL provides an extensive modular optimization framework for prototyping reconstruction methods including sparsity and total variation regularization, as well as tools for loading, preprocessing and visualizing tomographic data. The capabilities of CIL are demonstrated on a synchrotron example dataset and three challenging cases spanning golden-ratio neutron tomography, cone-beam X-ray laminography and positron emission tomography. This article is part of the theme issue 'Synergistic tomographic image reconstruction part 2'.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Programas Informáticos
/
Interpretación de Imagen Radiográfica Asistida por Computador
/
Tomografía Computarizada por Rayos X
Límite:
Humans
Idioma:
En
Revista:
Philos Trans A Math Phys Eng Sci
Asunto de la revista:
BIOFISICA
/
ENGENHARIA BIOMEDICA
Año:
2021
Tipo del documento:
Article
País de afiliación:
Dinamarca