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DEEPCT

Tomographic reconstruction for low-dose x-ray systems using deep learning

X-ray tomography equipment makes it possible to obtain quality tomographic images but with the main drawbacks of high radiation dose for the patient, avoiding its indication in pediatric applications or for repetitive or screening tests, and the fact that the patient must be completely positioned inside the scanner gantry, which makes its use impossible in cases where there are patient mobility difficulties (in the ICU or during surgery, for example). The recent technical solutions for obtaining tomographic images from limited data (angular coverage of less than 360 degrees) enables the use of these technologies in situations where it is difficult to have a CT scanner available (in an ambulance, for example).

Image reconstruction from limited angle data with a reduced number of projections and not a standard tomographic geometry, requires the development of new techniques to compensate for the lack of data. One possible approach involves the integration of Deep Learning technologies. The main disadvantage of iterative reconstruction algorithms is the computational time, which is a limitation for their use in this type of environment where it is crucial to maintain the real-time condition, so that decisions can be made at the same moment in the operating room or in the ambulance. For these reasons, it is necessary to explore the possibilities of developing these algorithms on non-traditional computing platforms with models and programming paradigms that can provide the necessary computational resources to obtain these images in times shorter than those obtained in traditional systems.

The ultimate goal of this project is to investigate advanced reconstruction methods for limited data using machine learning based techniques and their implementation using GPU based optimization strategies.

Team

  • Mónica Abella García (PI)
  • Javier Garcia-Blas (PI)
  • Carlos Fernández del Cerro
  • Aida de la Fe Pena Gil
  • Agustín Galán González
  • Cristóbal Martínez Sánchez
  • Patricia Moreno Berdón

Publications

Journals

  • Optimization design of a calibration for quantitative radiography 2020C. de Molina, C. Martínez, M. Desco, M. Abella. 10.1002/mp.14638

  • Simplified Statistical Image Reconstruction for X-ray CT with Beam-Hardening Artifact Compensation2020M. Abella, C. Martinez, M. Desco, Jeffrey A. Fessler. 10.1002/mp.14638

  • Accelerated Image Reconstruction for Low-dose Computed Tomography through Big Data Frameworks2020E. Serrano, J. García-Blas, J. Carretero, M. Desco, M. Abella. 10.1016/j.future.2019.12.042

Conferences

XXXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica – Celebrado On-lineHerramienta de pegado de múltiples camas para tomografía computarizada en 3D mediante dispositivos GPU2020J. Garcia-Blas, P. Brox, J. Carretero, M. Desco y M. Abella.

XXXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica – Celebrado On-lineMétodo de calibración geométrica para tomosíntesis de tórax2020G. González, A. D. V. Hidalgo, J. Garcia-Blas, M. D. Menéndez y M. Abella

XXXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica – Celebrado On-lineMétodo de reconstrucción tomográfica con información a priori obtenida con aprendizaje profundo2020A. Piol, C. F. D. Cerro, J. Garcia-Blas, M. Desco y M. Abella

XXXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica – Celebrado On-lineEfecto de los parámetros geométricos de adquisición en tomosíntesis digital lineal2020A. V. del Hidalgo, A. G. González, J. Garcia-Blas, M. Desco y M. Abella

XXXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica – Celebrado On-lineNuevo método para la obtención de imágenes TAC libres de endurecimiento de haz vía aprendizaje automático2020C. Martínez, C. F. Del Cerro, M. Desco, M. Abella

XXXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica – Celebrado On-lineCorrección del Artefacto de Truncamiento en TAC mediante Aprendizaje profundo. 2020P. M. Berdón, C. F. Del Cerro, R. C. Gimenez, M. Desco, M. Abella

XXXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica – Celebrado On-lineNuevo método para la obtención de imágenes TAC libres de endurecimiento de haz vía aprendizaje automático2020Martínez, C. F. Del Cerro, M. Desco, M. Abella.

XXXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica – Celebrado On-lineCompensación de radiación dispersa en radiografía digital a través del aprendizaje automático: resultados preliminares2020N. Sakaltras, F. A. Tovar, C. Martinez, C. F. Del Cerro, M. Desco, M. Abella

6th International Conference on Image Formation in X-Ray Computed Tomography (CT meeting) Prior Information for CT Reconstruction from Thermal Data2020A. Piol, P. M. Berdon, M. Desco, M. Abella

6th International Conference on Image Formation in X-Ray Computed Tomography (CT meeting) Segmentation-Free Statistical Method for Polyenergetic X-Ray Computed Tomography with a Calibration Step2020C. Martínez, J. A. Fessler, M. Desco, M. Abella

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