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Manual adjustment of brain extraction parameters in a volumetric study

Ivan Dimitrov, Radoslav Georgiev, Nataliya Usheva


INTRODUCTION: Brain volumetry is a contemporary method used in scientific and clinical research in neurodegenerative diseases. The process can be fully automated but it allows some parameters to be manually adjusted in order to minimize errors. The purpose of the present study is to analyze the use of additional settings in the process of extracting brain tissue from the skull in volumetric assessments performed using FSL-SIENAX, to point out the most frequently used ones, and to provide recommendations for their application.

MATERIAL AND METHODS: 3DT1 MRI scans of 51 patients with multiple sclerosis were processed. After conversion from the native format, brain tissue was extracted using the BET procedure. Multiple experiments were done using different parameters followed by a visual assessment of the results. Optimal values were chosen for each case. Descriptive statistical analysis was performed.

RESULTS: Manual corrections of the default settings of BET were made in all studied cases. The most frequently applied parameter (100% of cases) was `-f`, which adjusts the aggressiveness of the algorithm, followed by `-B` (51%), which reduces bias field and neck voxels, `-R` (31,4%), multiple iterations of the algorithm, `-g` (25,5%), correction of the vertical gradient, `-S` (2%), removal of wrongfully identified optic nerves and eyeballs.

CONCLUSION: The fully automatic volumetric assessment of the brain performed by FSL-SIENAX accelerates the workflow, but may lead to imperfections in the results. Manual adjustment trials may begin with the "-f" parameter, followed by "-Ð’", "-R", "-g", and combinations between them.


BET; brain extraction; multiple sclerosis; SIENAX; volumetric study

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About The Authors

Ivan Dimitrov

Radoslav Georgiev
Medical university of Varna

Department of Imaging Diagnostics and Radiotherapy

Nataliya Usheva
Medical university of Varna

Department of Social Medicine and Health Care Organisation

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