ensure all caps when needed

Author: oesteban

fmriprep/data/boilerplate.bib

@@ -111,7 +111,7 @@ @article{fsl_fast
     journal = {IEEE Transactions on Medical Imaging},
     number = 1,
     pages = {45-57},
-    title = {Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm},
+    title = {Segmentation of brain {MR} images through a hidden Markov random field model and the expectation-maximization algorithm},
     volume = 20,
     year = 2001
 }
@@ -123,7 +123,7 @@ @article{fieldmapless1
     issn = {1662-5196},
     journal = {Frontiers in Neuroinformatics},
     language = {English},
-    title = {Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI},
+    title = {Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion {MRI}},
     url = {http://journal.frontiersin.org/article/10.3389/fninf.2017.00017/full},
     volume = 11,
     year = 2017
@@ -134,7 +134,7 @@ @phdthesis{fieldmapless2
     author = {Huntenburg, Julia M.},
     language = {eng},
     school = {Freie Universität},
-    title = {Evaluating nonlinear coregistration of BOLD EPI and T1w images},
+    title = {Evaluating nonlinear coregistration of {BOLD} {EPI} and T1w images},
     type = {Master's Thesis},
     url = {http://hdl.handle.net/11858/00-001M-0000-002B-1CB5-A},
     year = 2014
@@ -159,12 +159,10 @@ @article{flirt
     issn = {1361-8415},
     url = {http://www.sciencedirect.com/science/article/pii/S1361841501000366},
     doi = {10.1016/S1361-8415(01)00036-6},
-    abstract = {Registration is an important component of medical image analysis and for analysing large amounts of data it is desirable to have fully automatic registration methods. Many different automatic registration methods have been proposed to date, and almost all share a common mathematical framework — one of optimising a cost function. To date little attention has been focused on the optimisation method itself, even though the success of most registration methods hinges on the quality of this optimisation. This paper examines the assumptions underlying the problem of registration for brain images using inter-modal voxel similarity measures. It is demonstrated that the use of local optimisation methods together with the standard multi-resolution approach is not sufficient to reliably find the global minimum. To address this problem, a global optimisation method is proposed that is specifically tailored to this form of registration. A full discussion of all the necessary implementation details is included as this is an important part of any practical method. Furthermore, results are presented for inter-modal, inter-subject registration experiments that show that the proposed method is more reliable at finding the global minimum than several of the currently available registration packages in common usage.},
     number = {2},
     urldate = {2018-07-27},
-    journal = {Med Image Anal},
+    journal = {Medical Image Analysis},
     author = {Jenkinson, Mark and Smith, Stephen},
-    month = jun,
     year = {2001},
     keywords = {Affine transformation, flirt, fsl, Global optimisation, Multi-resolution search, Multimodal registration, Robustness},
     pages = {143--156}
@@ -203,7 +201,7 @@ @article{aroma
     number = {Supplement C},
     pages = {267-277},
     shorttitle = {ICA-AROMA},
-    title = {ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data},
+    title = {ICA-{AROMA}: A robust {ICA}-based strategy for removing motion artifacts from fMRI data},
     url = {http://www.sciencedirect.com/science/article/pii/S1053811915001822},
     volume = 112,
     year = 2015
@@ -254,8 +252,9 @@ @article{compcor
     journal = {NeuroImage},
     number = 1,
     pages = {90-101},
-    title = {A component based noise correction method (CompCor) for BOLD and perfusion based fMRI},
+    title = {A component based noise correction method ({CompCor}) for {BOLD} and perfusion based fMRI},
     url = {http://www.sciencedirect.com/science/article/pii/S1053811907003837},
     volume = 37,
     year = 2007
 }
+