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Main contributions by topic

Juan F P J Abascal, but in the past I have also signed as J F Perez-Juste Abascal and J Abascal

Spectral CT
Material decomposition
  • JFPJ Abascal, N Ducros, F Peyrin. Nonlinear material decomposition using a regularized iterative scheme based on the Bregman distance, Inverse Problems 34 124003, 2018. DOI: 10.1088/1361-6420/aae1e7 PDF.   

  • N Ducros, JFPJ Abascal, B Sixou, S Rit, F Peyrin. Regularization of Nonlinear Decomposition of Spectral X-ray Projection Images. Med Phys, 44(9):e174-e187, 2017. DOI: 10.1002/mp.12283 (MATLAB code: SPRAY ToolboxPDF

  • ​N Ducros, O Pivot, S Rit, JM Létang, JFPJ Abascal, Y Boursier, M Dupont, C Morel, F Peyrin. Imagerie X spectrale: Décomposition en base de matériaux par calibration polynomiale. Recherche en Imagerie et Technologies pour la Santé (RITS) 2017, Mar 2017, Lyon, France

Osteoarthritis​​
  • C Garcelon. et al. Quantification of cartilage and subchondral bone cysts on knee specimens based on a spectral photon-counting computed tomography. Scientific Reports 13 (1), 11080, (2022). PDF

  • Chappard, C., Abascal, J., Olivier, C. et al. Virtual monoenergetic images from photon-counting spectral computed tomography to assess knee osteoarthritis. Eur Radiol Exp 6, 10 (2022). PDF

  • S BUSSOD, JFPJ Abascal, N Ducros, C Olivier, S Si-Mohamed, P Douek, C CHAPPARD, F Peyrin. Human Knee Phantom for Spectral CT: Validation of a Material Decomposition Algorithm. IEEE 16th International Symposium on Biomedical Imaging (ISBI), 2019

  • C Chappard, JFPJ Abascal, S Bussod, S Uk, S S. Si-Mohamed, P Douek, F Peyrin2. Feasibility of photon counting spectral CT to assess knee cartilage. Quantitative Musculoskeletal Imaging (QMSKI), 2019

Others
  • G Landry, F Dörringer, S Si-Mohamed, P Douek, JFPJ Abascal, F Peyrin, IP Almeida, F Verhaegen, I Rinaldi, K Parodi, S Rit. Technical Note: Relative proton stopping power estimation from virtual monoenergetic images reconstructed from dual-layer computed tomography. Med Phys, 46(4): 1821-1828, 2019. DOI: 10.1002/mp.13404

Split Bregman method
  • JFPJ Abascal, N Ducros, F Peyrin. Nonlinear material decomposition using a regularized iterative scheme based on the Bregman distance, Inverse Problems 34 124003, 2018. DOI: 10.1088/1361-6420/aae1e7 PDF.   

Fluorescence optical tomography
  • J Chamorro-Servent, J F P J Abascal, J Aguirre, S Arridge, T Correia, J Ripoll, M Desco, J J Vaquero. Use of Split Bregman denoising for iterative reconstruction in fluorescence diffuse optical tomography. J Biomed Opt, 18(7):076016, 2013. DOI: http://dx.doi.org/10.1117/1.JBO.18.7.076016. (MATLAB codePDF 

  • JF P-J Abascal, J Aguirre, J Chamorro-Servent, M Schweiger, S Arridge, J Ripoll, JJ Vaquero, M Desco. Influence of Absorption and Scattering on the Quantification of Fluorescence Diffuse Optical Tomography using Normalized Data. J Biomed Opt, 17(3): 036013-1 - 036013-9, 2012. DOI: http://dx.doi.org/10.1117/1.JBO.17.3.036013. PDF

  • Abascal JF, Chamorro-Servent J, Aguirre J, Arridge S, Correia T, Ripoll J, Vaquero JJ, Desco M. Fluorescence diffuse optical omography using the split Bregman method. Med Phys. 38(11):6275-84, 2011
  • T Correia, J Aguirre, A Sisniega, J Chamorro-Servent, J Abascal, JJ Vaquero, M Desco, V Kolehmainen, and S Arridge. Split operator method for fluorescence diffuse optical tomography using anisotropic diffusion regularisation with prior anatomical information. Biomedical Optics Express 2(9), 2632-2648, 2011. DOI: 10.1364/BOE.2.002632. PDF

Electrical impedance tomography
Anisotropic EIT
  • Juan-Felipe P J Abascal, William R B Lionheart, Simon R Arridge, Martin Schweiger, David Atkinson and David S Holder. Electrical impedance tomography in anisotropic media with known eigenvectors. Inverse Problems 27, 65004, 2011. DOI: 10.1088/0266-5611/27/6/065004 PDF 

  • Juan-Felipe P.J. Abascal, Simon R. Arridge, David Atkinson, Raya Horesh, Lorenzo Fabrizi, Marzia De Lucia, Lior Horesh, Richard H. Bayford, David S. Holder. Use of anisotropic modelling in electrical impedance tomography; Description of method and preliminary assessment of utility in imaging brain function in the adult head. NeuroImage 43 (2), 258-268, 2008. DOI: 10.1016/j.neuroimage.2008.07.023 PDF

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  • Abascal JF, Arridge SR, Lionheart WR, Bayford RH, Holder DS. Validation of a finite-element solution for electrical impedance tomography in an anisotropic medium. Physiol. Meas. 28, S129-S140, 2007. (Selected paper by IOP.) DOI: 10.1088/0967-3334/28/7/S10 PDF

  • J F P J Abascal. Improvements in reconstruction algorithms for electrical Impedance Tomography of brain function. Ph.D. thesis, Dept. of Medical Physics and Bioengineering, University College London, UK, 2007. PDF

  • Juan Felipe Pérez-Juste Abascal. The anisotropic inverse conductivity problem. MSc Thesis, Dept. of Mathematics, The University of Manchester, UK, 2003. 

Linear inverse problems
  • Juan-Felipe P J Abascal, Simon R Arridge, Richard H Bayford and David S Holder. Comparison of methods for optimal choice of the regularization parameter for linear electrical impedance tomography of brain function. Physiol. Meas. 29, 1319-1334, 2008. DOI: 10.1088/0967-3334/29/11/007 PDF 

  • J F P J Abascal. Improvements in reconstruction algorithms for electrical Impedance Tomography of brain function. Ph.D. thesis, Dept. of Medical Physics and Bioengineering, University College London, UK, 2007. PDF

Shape reconstruction
  • M. Soleimani, Juan Felipe P. J. Abascal and William R.B. Lionheart. Simultaneous reconstruction of the boundary shape and conductivity in 3D electrical impedance tomography. Conference on Electrical Bioimpedance and Electrical Impedance Tomography, Gdansk, Poland, 20-24 June 2004. 

Epilepsy
  • L Fabrizi, M Sparkes, L Horesh, J F Perez-Juste Abascal, A McEwan, R H Bayford, R Elwes, C D Binnie and D S Holder. Factors limiting the application of electrical impedance tomography for identification of regional conductivity changes using scalp electrodes during epileptic seizures in humans. Physiol. Meas., 27, S163-S174, 2006. DOI: http://dx.doi.org/10.1088/0967-3334/27/5/S14

  • L. Fabrizi, L. Horesh, J. F. Perez-Juste Abascal, A. McEwan, O. Gilad, R. Bayford and D. S. Holder (2011). Determination of Optimal Parameters and Feasibility for Imaging of Epileptic Seizures by Electrical Impedance Tomography: A Modelling Study Using a Realistic Finite Element Model of the Head, Applied Biomedical Engineering, Dr. Gaetano Gargiulo (Ed.), ISBN: 978-953-307-256-2. DOI: http://dx.doi.org/10.5772/25015

Multifrequency EIT

  • A Romsauerova, R Yerworth, A McEwan, L Horesh, JFPJ Abascal, DS Holder. Calibration and preliminary human measurements for multifrequency EIT of the human head. Calibration and preliminary human measurements for multifrequency EIT of the human head. VI International Conference on Biomedical Applications of Electrical Impedance Tomography, London, UK, 2005 ​

Deep learning​
  • V Pronina, AL Mur, JFPJ Abascal, F Peyrin, DV Dylov, N Ducros. 3D denoised completion network for deep single-pixel  reconstruction of hyperspectral images, Optics Express 29 (24), 39559-39573, 2021. (PDF​)

  • JFPJ Abascal, N Ducros, et al.. Material Decomposition in Spectral CT using deep learning: A Sim2Real transfer approach, IEEE Accesss, 2020 ⟨PDF⟩​

 

  • JFPJ Abascal, S Bussod, N Ducros, S Si-Mohamed, C Chappard, P Douek, F Peyrin. A residual U-Net network with image prior for 3D image denoising, European Signal Processing Conference, 2020, (preprint PDF)

  • JFPJ Abascal, N Ducros, V Pronina, S Bussod, P Douek, S Arridge, A Hauptmann, F Peyrin. Material Decomposition Problem in Spectral CT: A Transfer Deep Learning Approach. IEEE Internat Sympos Biomed Imaging (ISBI), Iowa, US, 2020. DOI: 10.1109/ISBIWorkshops50223.2020.9153440. (preprint PDF)

  • JFPJ Abascal, N Ducros, V Pronina, S Bussod, P Douek, S Arridge, A Hauptmann, F Peyrin. Nonlinear material decomposition in spectral CT using deep learning. Applied Inverse Problems conference, Grenoble, 2019

Machine learning 
  • JFPJ Abascal, SR Arridge, R Bayford, DS Holder. Improvement of image quality in Electrical Impedance Tomography of neonatal visual evoked responses using Principal Component Analysis, 208, (report PDF)

Sparsity and compressed sensing
Denoising
  • JFPJ Abascal, S. Si-Mohamed, P Douek, C Chappard, F Peyrin. A sparse and prior based method for 3D image denoising,  European Signal Processing Conference (EUSIPCO), 2019 (PDF)

Compressed sensing MRI ​​
  • JFPJ Abascal, Manuel Desco and J Parra-Roble. Incorporation of prior knowledge of the signal behavior into the reconstruction to accelerate the acquisition of MR diffusion data. IEEE Trans Med Imaging, 2017. DOI: 10.1109/TMI.2017.2765281. (MATLAB code)​ PDF 

  • C Chavarrias, JFPJ Abascal, P Montesinos, M Desco. Exploitation of temporal redundancy in compressed sensing reconstruction of fMRI studies with a prior-based algorithm (PICCS), Med Phys, 42(7): 3814 , 2015. DOI: 10.1118/1.4921365  (MATLAB codePDF

 

  • J F P J Abascal, P Montesinos, E Marinetto, J Pascau, M Desco. Comparison of total variation with a motion estimation based compressed sensing approach for self-gated cardiac cine MRI in small animal studies. PLOS ONE 9(10): e110594, 2014. DOI: 10.1371/journal.pone.0110594 (MATLAB code) PDF 

  • P Montesinos, JFPJ Abascal, C Chavarrías, JJ Vaquero, M Desco. Compressed Sensing for Cardiac MRI Cine Sequences: A Real Implementation on a Small-Animal Scanner. XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013, IFMBE Proceedings: 214-217, 2014. DOI: http://dx.doi.org/10.1007/978-3-319-00846-2_53. PDF 

  • P Montesinos, J F P J Abascal, L Cussó, J J Vaquero, M Desco. Application of the compressed sensing technique to self-gated cardiac cine sequences in small animals. Magn Reson Med., 72(2): 369–380, 2013. DOI: 10.1002/mrm.24936 (MATLAB code) PDF

Compressed sensing CT
  • C. Goubet, M. Langer, F. Peyrin, J. F. P. J. Abascal. LOW-DOSE SYNCHROTRON NANO-CT VIA COMPRESSED SENSING. Proc in ISBI, 2018. PDF

  • JFPJ Abascal, M Abella, C Mory, N Ducros, C de Molina, E Marinetto, F Peyrin, M Desco. Sparse reconstruction methods in x-ray CT. Proc in  SPIE Optical Engineering + Applications - Developments in X-Ray Tomography XI (2017), San Diego, US.  http://dx.doi.org/10.1117/12.2272711. PDF

  • J F P J Abascal, M Abella, E Marinetto, J Pascau, and M Desco. A Novel Prior- and Motion-Based Compressed Sensing Method for Small-Animal Respiratory Gated CT.  PLOS ONE 9;11(3):e0149841, 2016.  DOI: 10.1371/journal.pone.0149841. (MATLAB Code) PDF

  • J F P J Abascal, M Abella, 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.  DOI: 10.1371/journal.pone.0120140. (Data) (MATLAB code) PDF

  • C de Molina, JFPJ Abascal, M Desco, M Abella. Study of the possibilities of Surface-Constrained Compressed Sensing (SCCS) Method for Limited-View Tomography in CBCT systems. Proceedings of 4th International Conference on Image Formation in X-Ray Computed Tomography, 2016 

  • M Abella, J F P J Abascal, E Marinetto, J J Vaquero, M Desco. Novel 4D Image Reconstruction for Dynamic X-Ray Computed Tomography in Slow Rotating ScannersIEEE Nuclear Science Symposium and Medical Imaging Conference (2014 NSS/MIC), 2014. DOI: 10.1109/NSSMIC.2014.7430935 ​

  • 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 Nuclear Science Symposium and Medical Imaging Conference (2014 NSS/MIC), 2014. DOI: 10.1109/NSSMIC.2014.7430937

Other regularization approaches
  • K  C Assi, E Gay, C Chnafa, S Mendez, F Nicoud, JFPJ Abascal, P Lantelme, F Tournoux, and D Garcia. Intraventricular vector flow mapping - A Doppler-based regularized problem with automatic model selection. Phys Med Biol 62(17):7131-7147, 2017. DOI: 10.1088/1361-6560/aa7fe7 PDF

Other applications
Magnetic induction tomography
  • F. Li, M. Soleimani, J. Abascal. Planar array magnetic induction tomography further improvement, Sensor Review, 39(2), 257-268, 2019. DOI: 10.1108/SR-02-2018-0027

  • F Li , JFPJ Abascal, M Desco, M Soleimani .Total variation regularization with split Bregman-based method in magnetic induction tomography using experimental data. IEEE Sensors Journal , 17(4),: 976 - 985, 2017. DOI: 10.1109/JSEN.2016.263741PDF 

 

ERT

  • B Chen, JFPJ Abascal, M Soleimani. Extended Joint Sparsity Reconstruction for Spatial and Temporal ERT Imaging. Sensors, 8(11), E4014, 2018. DOI: 10.3390/s18114014.

  • Chen, B.; Abascal, J.F.P.J.; Soleimani, M. Electrical Resistance Tomography for Visualization of Moving Objects Using a Spatiotemporal Total Variation Regularization Algorithm. Sensors, 18, 1704, 2018. DOI: 10.3390/s18061704.

ECT

  • C. Tholin-Chittenden, J. F. P. Abascal and M. Soleimani. Automatic Parameter Selection of Image Reconstruction Algorithms for Planar Array Capacitive Imaging, IEEE Sensors Journal, 18(15), 6263-6272, 2018. DOI: 10.1109/JSEN.2018.2844549

Eddy current imaging
  • Abascal, J.F.P.J.; Lambert, M.; Lesselier, D.; Dorn, O. 3D Eddy-Current imaging of metal tubes by gradient-based, controlled evolution of level sets. IEEE Transactions on Magnetics 44 (12), 4721-4729 , 2008. DOI: 10.1109/TMAG.2008.2004265 PDF

  • J.F. Abascal, M. Lambert, D. Lesselier, O. Dorn. Nonlinearized mapping of volumetric defects affecting a metal tube. Electromagnetic Non--Destructive Evaluation (XII), Y.-K. Shin and H.-B. Lee and S.-J. Song (Ed.), 172—179 Seoul, Korea, 2009. (ISBN: 978-1-60750-023-0). DOI: http://dx.doi.org/10.3233/978-1-60750-023-0-172

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PET
  • JFPJ Abascal, E Lage, JL Herraiz, ME Martino, M Desco, and JJ Vaquero. Dynamic PET Reconstruction using the split Bregman formulation. IEEE Nuclear Science Symposium and Medical Imaging Conference (2016 NSS/MIC), 2016

  • J F P J Abascal, E Lage, M E Martino, J L Herraiz, M Desco, J J Vaquero. Spatiotemporal Total Variation reconstruction for Dynamic PET. IEEE Nuclear Science Symposium and Medical Imaging Conference (2014 NSS/MIC), 2014. PDF​​​​​

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