Segmentation of Brain Tumor in 3D Intraoperative Ultrasound Imaging.

Abstract

BACKGROUND\nIntraoperative Ultrasound (iUS), using a navigation system and preoperative magnetic resonance imaging (pMRI), supports the surgeon intraoperatively in identifying tumor margins. Therefore, visual tumor enhancement can be supported by efficient segmentation methods.\n\n\nMETHODS\nA semi-automatic and two registration-based segmentation methods are evaluated to extract brain tumors from 3D-iUS data. The registration-based methods estimated the brain deformation after craniotomy based on pMRI and 3D-iUS data. Both approaches use the Normalized Gradient Field (NGF) and Linear Correlation of Linear Combinations (LC2 ) metrics. Proposed methods were evaluated on 66 B-mode and contrast-mode 3D-iUS data with metastasis and glioblastoma.\n\n\nRESULTS\nThe semi-automatic segmentation achieved superior results with Dice Similarity Index (DSI) values between [85.34, 86.79] % and Contour Mean Distance (CMD) values between [1.05, 1.11] mm for both modalities and tumor classes.\n\n\nCONCLUSIONS\nBetter segmentation results were obtained for metastasis detection than glioblastoma, preferring 3D-intraoperative B-mode over 3D-intraoperative contrast-mode. This article is protected by copyright. All rights reserved.