Validation of a Fully Automatic Method for the Routine Selection of the Anterior and Posterior Commissures in Magnetic Resonance Images
Open Access
- 24 March 2009
- journal article
- research article
- Published by S. Karger AG in Stereotactic and Functional Neurosurgery
- Vol. 87 (3), 148-154
- https://doi.org/10.1159/000209295
Abstract
The anterior and posterior commissures (AC and PC) typically form the reference points of the stereotactic coordinate system. Hence any discussion of target localization is limited by the variability of AC and PC selection. In an earlier study, which was performed using manual selections of AC and PC by 43 neurosurgeons, we showed that intersurgeon variability has a substantial impact on the localization of deep brain stimulation targets. We have developed and validated a fully automatic and robust AC and PC selection system that can be routinely used clinically. In this study, we show that this system is capable of localizing the AC and PC points with an accuracy that is better than that achieved clinically by manual selection, 0.65 mm (95% confidence interval: 0.56–0.79) versus 1.21 mm (95% confidence interval: 0.91–1.47) for AC and 0.56 mm (95% confidence interval: 0.46–0.66) versus 1.06 mm (95% confidence interval: 0.82–1.26) for PC.Keywords
This publication has 8 references indexed in Scilit:
- Intersurgeon Variability in the Selection of Anterior and Posterior Commissures and Its Potential Effects on Target LocalizationStereotactic and Functional Neurosurgery, 2008
- Computer-aided placement of deep brain stimulators: from planningto intraoperative guidanceIEEE Transactions on Medical Imaging, 2005
- Automatic Selection of DBS Target Points Using Multiple Electrophysiological AtlasesLecture Notes in Computer Science, 2005
- Performance-Based Classifier Combination in Atlas-Based Image Segmentation Using Expectation-Maximization Parameter EstimationIEEE Transactions on Medical Imaging, 2004
- Simultaneous Truth and Performance Level Estimation (STAPLE): An Algorithm for the Validation of Image SegmentationIEEE Transactions on Medical Imaging, 2004
- The adaptive bases algorithm for intensity-based nonrigid image registrationIEEE Transactions on Medical Imaging, 2003
- Multimodality image registration by maximization of mutual informationIEEE Transactions on Medical Imaging, 1997
- Multi-modal volume registration by maximization of mutual informationMedical Image Analysis, 1996