Paper Info
Title
A Cross Validation Study of Deep Brain Stimulation Targeting: From Experts to Atlas-Based, Segmentation-Based and Automatic Registration Algorithms
Abstract
Validation of image registration algorithms is a diffi- cult task and open-ended problem, usually application-dependent. In this paper, we focus on deep brain stimulation (DBS) targeting for the treatment of movement disorders like Parkinson's disease and essential tremor. DBS involves implantation of an electrode deep inside the brain to electrically stimulate specific areas shut- ting down the disease's symptoms. The subthalamic nucleus (STN) has turned out to be the optimal target for this kind of surgery. Unfortunately, the STN is in general not clearly distinguishable in common medical imaging modalities. Usual techniques to infer its location are the use of anatomical atlases and visible surrounding landmarks. Surgeons have to adjust the electrode intraoperatively using electrophysiological recordings and macrostimulation tests. We constructed a ground truth derived from specific patients whose STNs are clearly visible on magnetic resonance (MR) T2-weighted images. A patient is chosen as atlas both for the right and left sides. Then, by registering each patient with the atlas using different methods, several estimations of the STN location are obtained. Two studies are driven using our proposed validation scheme. First, a comparison between different atlas-based and nonrigid registration algorithms with a evaluation of their perfor- mance and usability to locate the STN automatically. Second, a study of which visible surrounding structures influence the STN location. The two studies are cross validated between them and against expert's variability. Using this scheme, we evaluated the expert's ability against the estimation error provided by the tested algorithms and we demonstrated that automatic STN targeting is possible and as accurate as the expert-driven techniques currently used. We also show which structures have to be taken into account to accurately estimate the STN location.
Year
DOI
Venue
2006
10.1109/TMI.2006.882129
IEEE Trans. Med. Imaging
Keywords
Field
DocType
altas-based segmentation, B-splines, deep brain stimulation, demons, nonrigid registration, preoperative targeting, surgical planning, validation
Computer vision,Deep brain stimulation,Surgical planning,Neurophysiology,Medical imaging,Segmentation,Algorithm,Image segmentation,Artificial intelligence,Cross-validation,Medicine,Image registration
Journal
Volume
Issue
ISSN
25
11
0278-0062
Citations 
PageRank 
References 
15
0.84
16
Authors
8
Name
Order
Citations
PageRank
F. Javier Sánchez Castro1383.73
Claudio Pollo21289.88
Reto Meuli3296107.65
Philippe Maeder48587.82
Olivier Cuisenaire525020.27
Meritxell Bach Cuadra632623.59
Jean-guy Villemure7806.22
Jean-Philippe Thiran82320257.56