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1.
Biomed Mater Eng ; 24(6): 3105-11, 2014.
Artículo en Inglés | MEDLINE | ID: mdl-25227019

RESUMEN

X-ray phase contrast computed tomography (CT) uses the phase shift that x-rays undergo when passing through matter, rather than their attenuation, as the imaging signal and may provide better image quality in soft-tissue and biomedical materials with low atomic number. Here a geometry-constraint-scan imaging technique for in-line phase contrast micro-CT is reported. It consists of two circular-trajectory scans with x-ray detector at different positions, the phase projection extraction method with the Fresnel free-propagation theory and the filter back-projection reconstruction algorithm. This method removes the contact-detector scan and the pure phase object assumption in classical in-line phase contrast Micro-CT. Consequently it relaxes the experimental conditions and improves the image contrast. This work comprises a numerical study of this technique and its experimental verification using a biomedical composite dataset measured at an x-ray tube source Micro-CT setup. The numerical and experimental results demonstrate the validity of the presented method. It will be of interest for a wide range of in-line phase contrast Micro-CT applications in biology and medicine.


Asunto(s)
Algoritmos , Intensificación de Imagen Radiográfica/métodos , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Tomografía Computarizada por Rayos X/métodos , Difracción de Rayos X/métodos , Fantasmas de Imagen , Reproducibilidad de los Resultados , Sensibilidad y Especificidad , Tomografía Computarizada por Rayos X/instrumentación , Difracción de Rayos X/instrumentación
2.
Biomed Mater Eng ; 24(6): 3287-93, 2014.
Artículo en Inglés | MEDLINE | ID: mdl-25227038

RESUMEN

X-ray computed tomography (CT) is a powerful clinical diagnosis tool and has been used widely in many clinical and biological settings. Metal artifacts, caused by high density implants, are commonly encountered in clinical CT applications, thereby affecting the detection of abnormal structures and undermining CT's diagnostic value. In this paper, we developed a metal artifact reduction approach based on image segmentation and forward-projection. We further demonstrate the usefulness of our approach by using a biomedical specimen consisting of muscles, bones and metals. Our aim is to remove the inaccurate metal artifact pixels in the original CT slices and exactly reconstruct the soft-tissue using the forward projections with no metal information. During the reconstruction, artifacts are reduced by replacing the metal projection using the forward projection. The presented work is of interest for CT biomedical applications.


Asunto(s)
Algoritmos , Artefactos , Metales , Prótesis e Implantes , Intensificación de Imagen Radiográfica/métodos , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Fantasmas de Imagen , Reproducibilidad de los Resultados , Sensibilidad y Especificidad , Relación Señal-Ruido
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