Publications by the researcher in collaboration with J. Pérez Beteta (14)

2019

  1. Correction to: Morphological MRI-based features provide pretreatment survival prediction in glioblastoma (European Radiology, (2019), 29, 4, (1968-1977), 10.1007/s00330-018-5758-7)

    European Radiology

  2. Morphological MRI-based features provide pretreatment survival prediction in glioblastoma

    European Radiology, Vol. 29, Núm. 4, pp. 1968-1977

2018

  1. A three-dimensional computational analysis of magnetic resonance images characterizes the biological aggressiveness in malignant brain tumours

    Journal of the Royal Society Interface, Vol. 15, Núm. 149

  2. Intratumoral heterogeneity in 18F-FDG PET/CT by textural analysis in breast cancer as a predictive and prognostic subrogate

    Annals of Nuclear Medicine, Vol. 32, Núm. 6, pp. 379-388

  3. Predictive and prognostic potential of volume-based metabolic variables obtained by a baseline 18F-FDG PET/CT in breast cancer with neoadjuvant chemotherapy indication

    Revista Espanola de Medicina Nuclear e Imagen Molecular, Vol. 37, Núm. 2, pp. 73-79

2017

  1. Glioblastoma: Pre-treatment geometry and texture of postcontrast T1 MRI matter

    2016 Conference on Design of Circuits and Integrated Systems, DCIS 2016 - Proceedings

  2. Glioblastoma: does the pre-treatment geometry matter? A postcontrast T1 MRI-based study

    European Radiology, Vol. 27, Núm. 3, pp. 1096-1104

  3. Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization

    PLoS ONE, Vol. 12, Núm. 6

  4. Metabolic Tumor Burden Assessed by Dual Time Point [18F]FDG PET/CT in Locally Advanced Breast Cancer: Relation with Tumor Biology

    Molecular Imaging and Biology, Vol. 19, Núm. 4, pp. 636-644

  5. Textural features and SUV-based variables assessed by dual time point 18F-FDG PET/CT in locally advanced breast cancer

    Annals of Nuclear Medicine, Vol. 31, Núm. 10, pp. 726-735

2016

  1. Brain tumor: textural heterogeneity as predictor of survival in Glioblastoma

    No Lineal 2016. International Conference on Nonlinear Mathematics and Physics: 7-10, 2016. book of abstracts (Juan F.R. Archilla), pp. 44-44

  2. Geometrical measures obtained from pretreatment postcontrast T1 weighted mris predict survival benefits from bevacizumab in glioblastoma patients

    PLoS ONE, Vol. 11, Núm. 8

  3. Influence of gray level and space discretization on brain tumor heterogeneity measures obtained from magnetic resonance images

    Computers in Biology and Medicine, Vol. 78, pp. 49-57

  4. Tumour heterogeneity in glioblastoma assessed by MRI texture analysis: A potential marker of survival

    British Journal of Radiology, Vol. 89, Núm. 1064