Alzheimer's Disease versus Bipolar Disorder versus Health Control MRI data and processed results

<p><strong>README</strong></p> <p>The data is structured as follows:</p> <p>Clinical_data folder contains the .csv that can be read by spreadsheet software, as well as from Python, Matlab or R. There are separate files for each biomarker. The file &quot;clinical_data_id_age_gender.csv&quot; contains the numerical random key of the patient for anonymity, diagnostic key, age and gender for each entry in the other files. The file &quot;clinical_data_corrected.csv&quot; can be ignored.</p> <p>Diagnostic keywords: &quot;crl&quot; == healthy control, &quot;tb&quot; == bipolar disorder, &quot;ea&quot; == Alheimer&#39;s disease</p> <p>Imaging data is nifti encoded. The name of the file starts with the diagnostic key followed by the numerical random key and some nemotechnic for the contents. For instance: &quot;crl_132_diff_dti_FA_FA_to_target.nii.gz&quot; is the spatially normalized FA data of healthy control 132. Imaging data can be read with FSL, SPM, and any other nifti reading soft.</p> <p>Imaging folders contain the following data<br> DWI_origin - &gt; the original diffusion weighted MRI data and their corresponding b-vector values</p> <p>FA - &gt; the FA coefficients computed using FSL</p> <p>FA_to_target - &gt; the FA volumes registered to MNI template using FSL tools</p> <p>T1_preprocessed - &gt; the T1-weighted volumes at 1mm resolution registered to the MNI template using FSL no-linear registration tools</p> <p>T1_VBM_SPM_1mm - &gt; the results of applying SPM implementation of voxel based morphometry (VBM) on the T1-weighted data, including results of the correlation between biomarkers and the detected clusters . Results can be checked using SPM (https://www.fil.ion.ucl.ac.uk/spm/)</p> <p>TBSS_results -&gt; contains track based spatial statistics (TBSS) results obtained with FSL software (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/TBSS)</p> <p>&nbsp;</p> <p><strong>Publications using this dataset</strong></p> <p>M. Gra&ntilde;a, M. Termenon, A. Savio, A. Gonzalez-Pinto, J. Echeveste, J. M. P&eacute;rez, A. Besga,&nbsp;Computer Aided Diagnosis system for Alzheimer Disease using brain Diffusion Tensor Imaging features selected by Pearson&rsquo;s correlation, &nbsp;Neuroscience letters,Volume 502, Issue 3, 20 September 2011, Pages 225-229</p> <p>A. Besga, M. Termenon, M. Gra&ntilde;a, J. Echeveste, J. M. Perez, A. Gonzalez-Pinto&nbsp;&quot;Discovering Alzheimer&#39;s disease and bipolar disorder white matter effects building computer aided diagnostic systems on brain diffusion tensor imaging features,&nbsp;<strong>Neuroscience Letters</strong>, Volume 520, Issue 1, 27 June 2012, Pages 71&ndash;76.</p> <p>M. Termenon, M. Gra&ntilde;a, A. Besga, J. Echeveste, A. Gonzalez-Pinto,&nbsp;Lattice Independent Component Analysis feature selection on Diffusion Weighted Imaging for Alzheimer&rsquo;s Disease Classification,&nbsp;Neurocomputing (2013) Volume 114, 19 August 2013, Pages 132&ndash;141</p> <p>Ariadna Besga, Itxaso Gonz&aacute;lez-Ortega, Enrique Echebur&uacute;a, Alexandre Savio, Borja Ayerdi, Darya Chyzhyk, Jose LM Madrigal, Juan C. Leza, Manuel Gra&ntilde;a, Ana Gonz&aacute;lez-Pinto, &nbsp;&quot;Discrimination between Alzheimer&rsquo;s Disease and Late Onset Bipolar Disorder using multivariate analysis&quot;&nbsp;Frontiers in Aging Neuroscience, 7:231</p> <p>Ariadna Besga-Basterra, Darya Chyzhyk, Itxaso Gonz&aacute;lez-Ortega, Alexandre Savio, Borja Ayerdi, Jon Echeveste, Manuel Gra&ntilde;a, Ana Gonz&aacute;lez-Pinto, &nbsp;Eigenanatomy on fractional anisotropy imaging provides white matter anatomical features discriminating between Alzheimer&rsquo;s Disease and Late Onset Bipolar Disorder,&nbsp;Current Alzheimer Research, 13(5): 557 - 565 (2016)</p> <p>Ariadna Besga, Darya Chyzhyk, Itxaso Gonzalez Ortega, Jon Echeveste, Marina Grana-Lecuona, Manuel Grana, Ana Gonz&aacute;lez-Pinto,&nbsp;White Matter Tract Integrity in Alzheimer&rsquo;s Disease versus Late Onset Bipolar Disorder and its Correlation with Systemic Inflammation and Oxidative Stress Biomarkers,&nbsp;Frontiers in Aging Neuroscience, 9:179 (2017)</p>