Fully Automated MRI Segmentation Allows Surgeons 3D Evaluation in Augmented Reality

Researchers in the Netherlands created and validated a cloud-based, automatic segmentation algorithm that generates 3D images from contrast-enhanced T1-weighted MR sequences. The resulting images can be used by surgeons for augmented reality (AR) viewing of brain tumors for evaluation and surgical planning, according to Erik Ridley of AuntMinnie.com

The team, led by Dr. Tim Fick, sought to overcome the lengthy process of manual or semi-automatic segmentation by creating the automated segmentation algorithm and building it into “an automatic workflow for 3D evaluation of anatomical structures with augmented reality in a cloud environment.”

Dr. Fick’s team concluded “The automatic cloud-based segmentation algorithm is reliable, accurate, and fast enough to aid neurosurgeons in everyday clinical practice by providing 3D augmented reality visualization of contrast-enhancing intracranial lesions measuring at least 5 cm3.”  Next steps “involve incorporation of other sequences and improving accuracy with 3D fine-tuning in order to expand the scope of augmented reality workflow.”


Fick, Tim, Jesse A. M. van Doormaal, Lazar Tosic, Renate J. van Zoest, Jene W. Meulstee, Eelco W. Hoving, and Tristan P. C. van Doormaal. “Fully automatic brain tumor segmentation for 3D evaluation in augmented reality”. Neurosurgical Focus 51.2 (2021): E14. < https://doi.org/10.3171/2021.5.FOCUS21200>. Web. 30 Aug. 2021. Accessed 30 Aug. 2021.

Ridley, Erik L. “Automated MR image segmentation enables AR use for surgeons.” AuntMinnie.com Available August 13, 2021. Accessed August 30, 2021, at https://www.auntminnie.com/index.aspx?sec=sup&sub=mri&pag=dis&ItemID=133225.