Publications

@article{ortiz-ramon_identification_2019,

title = {Identification of the presence of ischaemic stroke lesions by means of texture analysis on brain magnetic resonance images},

author = {Rafael Ortiz-Ramón and Maria del Carmen Valdés-Hernández and Victor González-Castro and Stephen Makin and Paul A Armitage and Benjamin S Aribisala and Mark E Bastin and Ian J Deary and Joanna M Wardlaw and David Moratal},

url = {https://www.sciencedirect.com/science/article/pii/S0895611119300278},

year  = {2019},

date = {2019-01-01},

journal = {Computerized Medical Imaging and Graphics},

volume = {74},

pages = {12–24},

abstract = {This study investigates using radiomics to detect stroke lesions in brain MRI scans, which are often missed by automated methods. Analyzing 1800 MRI scans, the research found that radiomic features could identify stroke lesions with accuracy between 0.7 and 0.83 AUC. Age was the clinical factor most correlated with accurate detection. The study suggests that incorporating texture features into deep learning models could improve stroke lesion detection in MRI scans.},

note = {Publisher: Pergamon},

keywords = {Radiomics, small vessel disease, Stroke, texture analysis, white matter hyperintensities},

pubstate = {published},

tppubtype = {article}

}

@article{valdes-hernandez_computational_2016,

title = {On the computational assessment of white matter hyperintensity progression: difficulties in method selection and bias field correction performance on images with significant white matter pathology},

author = {Maria del Carmen Valdés-Hernández and Victor González-Castro and Dina T Ghandour and Xin Wang and Fergus Doubal and Susana Muñoz-Maniega and Paul A Armitage and Joanna M Wardlaw},

url = {https://link.springer.com/article/10.1007/s00234-016-1648-3},

year  = {2016},

date = {2016-01-01},

journal = {Neuroradiology},

volume = {58},

pages = {475–485},

abstract = {Subtle inhomogeneities in the scanner’s magnetic fields (B0 and B1) alter the intensity levels of the structural magnetic resonance imaging (MRI) affecting the volumetric assessment of WMH changes. Here, we investigate the influence that (1) correcting the images for the B1 inhomogeneities (i.e. bias field correction (BFC)) and (2) selection of the WMH change assessment method can have on longitudinal analyses of WMH progression and discuss possible solutions.},

note = {Publisher: Springer Berlin Heidelberg},

keywords = {cerebrovascular disorders, leukoencephalopathies, MRI, neuroimaging, white matter hyperintensities},

pubstate = {published},

tppubtype = {article}

}