ResectVol: A tool to automatically segment and characterize lacunas in brain images.

ABSTRACT:

Objective

To assess and validate the performance of a new tool developed for segmenting and characterizing lacunas in postoperative MR images of epilepsy patients.

Methods

A MATLAB-based pipeline was implemented using SPM12 to produce the 3D mask of the surgical lacuna and estimate its volume. To validate its performance, we compared the manual and automatic lacuna segmentations obtained from 51 MRI scans of epilepsy patients who underwent temporal lobe resections.

Results

The code is consolidated as a tool named ResectVol, which can be run via a graphical user interface or command line. The automatic and manual segmentation comparison resulted in a median Dice similarity coefficient of 0.77 (interquartile range: 0.71-0.81).

Significance

Epilepsy surgery is the

SUBMITTER: Casseb RF 

PROVIDER: S-EPMC8633465 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature