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8 March 2019 Evaluation of nonrigid registration around the hippocampus for the construction of statistical maps in a multicenter dataset of epilepsy laser ablation patients
Author Affiliations +
Abstract
Laser interstitial thermal therapy (LITT) is a novel minimally-invasive neurosurgical ablative tool that is par ticularly well-suited for treating patients suffering from drug-resistant mesial temporal lobe epilepsy (mTLE). Although morbidity to patients is lower with LITT compared to the open surgical gold standard, seizure freedom rates appear inferior, likely a result of our lack of knowledge of which mesial temporal subregions are most critical for treating seizures. The wealth of post-LITT imaging and outcomes data provides a means for elucidating these critical zones, but such analyses are hindered by variations in patient anatomy and the distribution of these novel data among multiple academic institutions, each employing different imaging and surgical protocols. Adequate population analyses of LITT outcomes require normalization of imaging and clinical data to a common reference atlas. This paper discusses a method to nonrigidly register preoperative images to an atlas and quantitatively evaluate its performance in our region of interest, the hippocampus. Knowledge of this registration error would allow us to both select an appropriate registration method and define our level of confidence in the correspondence of the postoperative images to the atlas. Once the registration process is validated, we aim to create a statistical map from all the normalized LITT ablation images to analyze and identify factors that correlate with good outcomes.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Srijata Chakravorti, Walter J. Jermakowicz, Chengyuan Wu, Rui Li, Raul Wirz-Gonzalez, Benoit M. Dawant, and Pierre-François D'Haese "Evaluation of nonrigid registration around the hippocampus for the construction of statistical maps in a multicenter dataset of epilepsy laser ablation patients", Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109511J (8 March 2019); https://doi.org/10.1117/12.2512587
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Image registration

Image segmentation

Epilepsy

Error analysis

Surgery

Laser ablation

Laser therapeutics

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