Mónica Abella

Learn More
Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. Image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp et al. (FDK). Besides the implementation of the reconstruction algorithm itself,(More)
This work reports on the development and performance evaluation of the VrPET/CT, a new multimodality scanner with coplanar geometry for in vivo rodent imaging. The scanner design is based on a partial-ring PET system and a small-animal CT assembled on a rotatory gantry without axial displacement between the geometric centers of both fields of view (FOV). We(More)
Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. Image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp, Davis and Kress (FDK). Currently there is a strong need to speedup the(More)
This paper presents a new statistical reconstruction algorithm for X-ray CT. The algorithm is based on Poisson statistics and a physical model that accounts for the measurement nonlinearities caused by energy-dependent attenuation. We model each voxel's attenuation as a mixture of bone and soft tissue by defining density-dependent tissue fractions,(More)
  • 1