Lesion Filling

Improve volume measurements by reducing intensity contrast within known lesion areas. It is intended for use with "small" lesions, such as those typical in Multiple Sclerosis.

Overview

This tool takes a user-defined lesion mask (usually created manually) together with a structural image (e.g. T1-weighted image, but it could also be T2-weighted, PD, etc.) and "fills" the lesion area in the structural image with intensities that are similar to those in the non-lesion neighbourhood. It has been shown (see references) that using such a method as part of a pre-processing pipeline can improve the registration and segmentation of pathological brains (particular those with Multiple Sclerosis) and the resultant volumetric measures of brain tissue.

If you are using this for larger lesions, such as stroke lesions, then be careful not to make the masks touch areas of non-brain tissue, as it uses the intensities immediately surrounding the mask to determine what intensities to fill the lesion with. When non-brain tissue touches the mask, the intensities of this tissue will be used in the filling process, which normally leads to results that do not look like brain tissue.

Referencing

If you use lesion_filling in your research, please make sure that you reference the article below.

Usage and options

The usage of the script is particularly simple and there are no configurable options.

Part of FSL (build 500)
lesion_filling 
Copyright(c) 2012, University of Oxford (Mark Jenkinson)

Usage: 
lesion_filling [options] -i <intensity image> -l <lesion mask image> -o <output/filled image>

Compulsory arguments (You MUST set one or more of):
        -i,--in input image filename (e.g. T1w image)
        -o,--out        output filename (lesion filled image)
        -l,--lesionmask filename of lesion mask image

Optional arguments (You may optionally specify one or more of):
        -v,--verbose    switch on diagnostic messages
        -h,--help       display this message