000124993 001__ 124993
000124993 005__ 20190117210500.0
000124993 0247_ $$2doi$$a10.1007/978-3-540-85990-1
000124993 02470 $$2ISI$$a000261373800118
000124993 037__ $$aCONF
000124993 245__ $$aAn Active Contour-based Atlas Registration Model for Automatic Subthalamic Nucleus Targeting on MRI: Method and Validation
000124993 269__ $$a2008
000124993 260__ $$aNew York, NY, USA$$bSpringer Berlin / Heidelberg$$c2008
000124993 336__ $$aConference Papers
000124993 490__ $$aLecture Notes in Computer Science$$v5242
000124993 520__ $$aThis paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert’s variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.
000124993 6531_ $$aLTS5
000124993 6531_ $$aRegistration
000124993 6531_ $$aActive Contours
000124993 6531_ $$aAtlas-based Segmentation
000124993 6531_ $$aDense Deformation field
000124993 6531_ $$aDeep Brain Stimulation
000124993 700__ $$aDuay, V.
000124993 700__ $$0241065$$aBresson, X.$$g140163
000124993 700__ $$aSanchez Castro, F. J.
000124993 700__ $$aPollo, C.
000124993 700__ $$0240463$$aBach Cuadra, M.$$g124931
000124993 700__ $$0240323$$aThiran, J.-Ph.$$g115534
000124993 7112_ $$a11th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)$$cNew York, NY, USA$$dSeptember 6-10, 2008
000124993 773__ $$j5242$$q980-988$$tMedical Image Computing and Computer-Assisted Intervention, MICCAI
000124993 8564_ $$uhttp://miccai2008.rutgers.edu/$$zURL
000124993 8564_ $$s540217$$uhttps://infoscience.epfl.ch/record/124993/files/fulltext.pdf$$zn/a
000124993 909C0 $$0252394$$pLTS5$$xU10954
000124993 909CO $$ooai:infoscience.tind.io:124993$$pconf$$pSTI$$qGLOBAL_SET
000124993 937__ $$aEPFL-CONF-124993
000124993 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000124993 980__ $$aCONF