X-Ray Imaging

Contact person: Mónica Abella

The work on X-ray Imaging encompasses all the steps of the image formation with X-rays from raw data acquisistion, calibration, pre-processing and tomographic reconstruction to post-processing and quantification. The work in this area can be divided into two main lines: "Clinical X-Ray systems" and "X-Ray CT systems for small animal".

  • Clinical X-Ray systems

The main objective of this line of research is the design and development of a new generation of Radiology systems, for clinical and veterinary applications, through the research and development of innovative technologies in advanced image processing oriented to increase image quality, to reduce dose and to incorporate tomography capabilities in Digital Radiology Systems. The latter would allow bringing tomography to situations in which a CT system is not allowable, for instance when the patient cannot be moved (during surgery or ICU) or due to costs issues (underdeveloped countries or rural areas). On the other hand, the reduction of radiation dose received by the patient will reduce risks involved in this imaging modality reducing the social reservations towards its use. 

  • X-Ray CT systems for small animal

The visualization and quantification of the function of certain organs in laboratory animals by means of nuclear medicine techniques is demonstrating to be a tool of great relevance for the characterization of the phenotype of transgenic animals in the study of models of human diseases, as well as for the discovery and development of the new drugs and biochemical probes. One of the difficulties that PET imaging must face working at the right scale for small animals is its relatively low spatial resolution, hindering the localization of the activated structures. This poses the urge of using other imaging modalities that provide anatomical information to localize functional data. X-ray CT is the anatomical modality preferred for small animal due to their high resolution and the possibility of being integrated with nuclear imaging systems. The combination of these systems enables synergies between both modalities, making it possible the use of the data acquired from one modality (CT) to process the data from the other (PET), for example to perform corrections or to help in the reconstruction with a priori information. In our laboratory we develop new technologies for high-resolution CT systems, some of which have been transferred to the industry.

Selected publications

A. García-Santos, C de Molina, I. García, A. Martínez, J. Pascau, M. Desco, M. Abella, Setting up a C-arm for its use as a tomograph, CASEIB 2015.

A. Marcos, A. Ortega, M. Abella, M. Desco, J. J. Vaquero, Geometric Calibration Workflow for High Resolution Cone Beam Micro-Computed Tomography, IEEE NSS/MIC, 2015

M. Abella, J. Abascal, A. Sisniega, J.J. Vaquero and M. Desco, Investigation of different sparsity transforms for the PICCS algorithm in small-animal respiratory gated CT, Plos One, 10(4), e0120140, 2015.

M. Abella, J. F. Abascal, E. Marinetto, J.J. Vaquero, M. Desco, Novel 4D Image Reconstruction for Dynamic X-Ray Computed Tomography in Slow Rotating Sanners, IEEE NSS/MIC, 2014

A Sisniega, M Abella, M Desco, JJ Vaquero. Dual exposure technique for extending the dynamic range of x-ray flat panel detectors. Phys Med Biol, vol. 59(2), 421-439, 2014

A. Sisniega, M. Desco and J. J. Vaquero, “Modification of the TASMIP x-ray spectral model for the simulation of microfocus x-ray sources”, Med. Phys., vol. 41, pp. 011902, 2014

J. Garcia Blas, M. Abella, F. Isaila, J. Carretero, M. Desco. Surfing the optimization space of a multiple-GPU parallel implementation of an X-ray tomography reconstruction algorithm, Journal of Systems and Software, 95, 166–175, 2014.

C. de Molina, J. F. P. J. Abascal, J. Pascau, M. Desco, M. Abella, Evaluation of the Possibilities of Limited Angle Reconstruction for the use of Digital Radiography System as a Tomograph, IEEE NSS/MIC, 2014

C de Molina, et al. Calibration of a C-arm X-Ray System for Its Use in Tomography. IFMBE Proceedings, 41: 245-248, 2013

A Sisniega, J Abascal, M Abella, J Chamorro, M Desco, JJ Vaquero. Iterative Dual-Energy Material Decomposition for Slow kVp Switching: A Compressed Sensing Approach. IFMBE Proceedings, 41: 491-494, 2013.

Sisniega, J. F. Abascal, M. Abella, M. Desco, J. J. Vaquero, Iterative Dual-Energy Raw Data Decomposition for Slow kVp Switching: a Feasibility Study, IEEE Nuclear Science Symposium and Medical Imaging Conference, 2948-2950, 2012

M Abella, JJ Vaquero, A Sisniega, J Pascau, A Udías, V García, I Vidal, M Desco. Software architecture for multi-bed FDK-based reconstruction in X-ray CT scanners. Comput Meth Prog Bio, 107(2): 218-232, 2012.

J Pascau, JJ Vaquero, J Chamorro-Servent, A Rodríguez-Ruano, M Desco. A method for small-animal PET/CT alignment calibration. Phys Med Biol, 57(12): N199-N207, 2012.

M Paraíso, et al. Evaluation of the effect of calibration accuracy in a C-arm for its use in tomography.  CASEIB  2012.

J Abascal, A Sisniega, C Chavarrías, JJ Vaquero, M Desco, M Abella. Investigation of different Compressed Sensing Approaches for Respiratory Gating in Small Animal CT. 2012 IEEE NSS/MIC, 3344-3346, 2012

M Abella, JA Fessler. A new statistical image reconstruction algorithm for polyenergetic X-ray CT. Proceedings of the 2009 IEEE ISBI, 165-168, 2009.


  1. IDI-20130301, “Nuevo sistema integral de radiografía (INNPROVE: INNovative image PROcessing in medicine and VEterinary)”, IP: Mónica Abella García and Manuel Desco Menéndez. Ministerio de Economía y Competitividad – Subcontratación CDTI, 14/01/2013-31/03/2015. (Art. 83)
  2. TEC2013-47270-R, “Avances en Imagen Radiológica (AIR)”, Ministerio de Economía y Competitividad, 01/01/2014-31/12/2016. IP: Mónica Abella García and Manuel Desco Menéndez.
  3. RTC-2014-3028-1, “Nuevos Escenarios Clínicos con Radiología Avanzada (NECRA)”, Ministerio de Economía y Competitividad, 01/06/2014-31/12/2016, IP: Mónica Abella García. 2014-2016.
  4. 120028/14, “Nuevo sistema integral de radiografía”, IP: Manuel Desco Menéndez, Fundación para la Innovación y Prospectiva de la Salud en España (FIPSE), IP: Manuel Desco Menéndez. 15/02/2015-14/02/2016.
  5. “Predict-TB: Model-based preclinical development of anti-tuberculosis drug combinations” Innovative Medicines Initiative (IMI) Joint Undertaking, EU-FP7, 2012-2015

Entidades Financiadoras



Fundación para la Innovación y Prospectiva de la Salud en España (FIPSE)

The research leading to these results has received funding from the Innovative Medicines Initiative (www.imi.europa.eu) Joint Undertaking under grant agreement n° 115337, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies' in kind contribution.


Mangoose, an efficient implementation of a multi-bed FDK-based reconstruction algorithm for CT scanners with cone-beam geometry, # 02/2010/4412, 2010. Licenciado a SEDECAL